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Job DescriptionCompany Description Columbia University's Pre-College Programs offer high-achieving high school students the opportunity to engage in exploratory coursework at the college level, studying alongside peers from around the world. This highly selective program is open to students entering grades 9 and through the summer following their senior year. Job Description Columbia University’s Pre-College Programs for high school students is seeking qualified candidates to develop and teach on-campus courses during Summer ’26. Reporting to the Senior Director of Instruction and Curriculum for Pre-College Programs, Pre-College instructors develop and deliver immersive non-credit courses for high-achieving high school students. They guide and supervise students when classes are in session, and write a holistic evaluation of each course participant after classes conclude. For more information on the program–including course sessions and times–please see here. Course Description This course traces knowledge of the universe from astronomy’s ancient roots to the modern study of extrasolar planetary systems, cosmology, and black holes. Topics include Newton’s laws of motion and universal gravitation, Kepler’s laws, orbital dynamics, and space travel. Additionally, students will contemplate the nature of light, the nature of matter, and nuclear physics. This knowledge to will be used to explore the properties of our sun, solar system, further galaxies, the creation of chemical elements, and the expansion of the universe. By the end of the course, students will be prepared to explore dark energy and the fate of the universe as we know it. Prerequisite: One year each of high school chemistry and physics are strongly recommended but not required. Because this class takes a quantitative approach, participants should be comfortable using their math skills to solve problems. Calculus is useful but not necessary. Course Schedule Session B: July 21 - August 7 -- 9:10 - 11:00am & 1:10 - 3:00pm Please note: Course(s) and course availability are subject to change. All times shown are Eastern Time (ET). Dates and class times are tentative and subject to change. Responsibilities: * Develop course content, syllabus, lesson plans, and assigned work, in accordance with Pre-College templates and regulations * Lead and attend all class sessions, including escorting students to and from campus for field trips * Establish and maintain a dynamic in-class environment tailored for our high school population * Evaluate student work and write a holistic evaluation of each participant after the course ends * Monitor and address student concerns and inquiries (typical class size is 20-24 students) * Attend and complete all required online trainings Qualifications • Graduate degree or equivalent professional or academic background, • Expertise in the pertinent subject matter, • Aptitude for teaching Additional Information Hiring Salary Range Session B (Campus, 3 Week): $7,000 - $9,000 • Please note your availability to teach the Session A schedule (as well as any information regarding your suitability for the role) in the Message to Hiring Manager field. Please submit a resume inclusive of teaching experience as well as formal teaching evaluations (if available) * Applicants must have U.S. work authorization and will need to be in the U.S. while teaching * Columbia Affiliates: There may be restrictions when hiring individuals who hold a concurrent appointment at Columbia University during the Summer term. Generally, PhD students and Officers of Research are not eligible. Please check with us during the hiring process regarding your eligibility. Please note, Pre-College courses do not count towards the maximum course loads for adjuncts. * Once hired, applicants are required to submit to a third party background check and complete Protection of Minors training in addition to other training(s) mandated by the University and Pre-College Program All your information will be kept confidential according to EEO guidelines. Columbia University is an Equal Opportunity Employer / Disability / Veteran

Vice President, Financial Model Risk Auditor At BNY, our culture allows us to run our company better and enables employees’ growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world’s investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide. Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance – and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary. We’re seeking a future team member for the role of Vice President, Auditor to join our Model Risk Audit Team within Internal Audit. This role is located in New York City, NY. In this role, you’ll make an impact in the following ways: • Performing high quality, risk-focused audit testing, in accordance with Internal Audit policies, methodologies, and standards in order to identify meaningful issues, risks and other exposures related to model risk in Finance’s Corporate Treasury functions, and Risk Management areas focusing on the Enterprise-wide management of Market Risk, Credit Risk, Interest Rate Risk, Liquidity Risk, Financial Crime Compliance (BSA / AML, and Artificial Intelligence / Machine Learning, and model governance., • Tests model development and model validation processes as per the Supervisory Guidance on Model Risk Management and the Bank’s Model Risk Management policies, standards, and procedures., • Operates as a team member or independently and has responsibility for specific procedures and results (i.e., head of a project relating to an audit, audit project, or model auditor). Ensures testing (or other tasks as applicable to a specialty) is adequately thorough and accurate to allow an evaluation of the adherence to company policies and procedures, audit methodologies, and all applicable regulations. Identifies existing and emerging risk/ control themes., • Prepare draft audit reports and follow-up of audit actions to ensure corrective actions have been appropriately implemented., • Learns new businesses, processes and regulations., • Work with other audit team members to mentor, guide and collaborate., • Work on projects of great complexity that involves significant understanding of the regulatory requirements, business models and processes for each assignment., • Maintain up to date knowledge of industry best practice and regulatory requirements., • Carry out other ad-hoc tasks and projects as directed by audit senior management., • Represent Internal Audit on projects and at management meetings., • Advanced degree (Masters or PhD) in Math, Statistics, Physics, Economics or other quantitative fields are required (PhD is preferred)., • Strong quantitative and analytical background coupled with strong theoretical foundation and good communication skills preferred., • 5+ years working experience in model development, model validation, or model audit in the risk area such as Market Risk, Credit Risk, Interest Rate Risk, Liquidity Risk, Financial Crime Compliance, Artificial Intelligence / Machine Learning, stress testing, and capital planning., • The position requires special skills (e.g. mathematical, statistical, quantitative, economic, and business knowledge and modeling experience)., • Proficient with programming languages used for model development and validation, such as Matlab, R, C, Python, etc.; Additional core skill requirements include understanding of the applied and interpretation of analytics results for Audit, critical thinking and problem solving At BNY, our culture speaks for itself, check out the latest BNY news at: Here’s a few of our recent awards: • America’s Most Innovative Companies, Fortune, 2025, • World’s Most Admired Companies, Fortune 2025, • “Most Just Companies”, Just Capital and CNBC, 2025 Our Benefits and Rewards: BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life’s journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter. BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans. BNY assesses market data to ensure a competitive compensation package for our employees. The base salary for this position is expected to be between $100,000 and $160,000 per year at the commencement of employment. However, base salary if hired will be determined on an individualized basis, including as to experience and market location, and is only part of the BNY total compensation package, which, depending on the position, may also include commission earnings, discretionary bonuses, short and long-term incentive packages, and Company-sponsored benefit programs. This position is at-will and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensatio

About the Company My client is a leading global investment management firm that delivers high-quality, uncorrelated returns through a diversified set of systematic and quantitative strategies across global financial markets. The firm’s success is driven by deep expertise in trading, technology, and operations, underpinned by rigorous scientific research. As a highly technology- and data-driven organization, it builds proprietary, cutting-edge systems ranging from high-performance trading platforms to large-scale data analytics and compute infrastructure. With a global footprint, the firm fosters true cross-border collaboration by aligning investment, technology, and operations teams worldwide. Complementing its systematic platform, the firm also runs discretionary strategies to capitalize on opportunities not well suited to purely systematic trading. About the Role Role/Responsibilities: Perform rigorous and innovative research to discover systematic anomalies in equity markets. Responsibilities • End-to-end development: alpha idea generation, data processing, strategy backtesting, optimization, and production implementation, • Identify and evaluate new datasets for stock return predictions, • Maintain and improve the portfolio trading in the production environment Qualifications • MS or PhD in physics, engineering, statistics, applied math, quantitative finance, or other quantitative fields with a strong foundation in statistics, • Previous experience within top hedge funds or investment banks as a quantitative researcher Required Skills • Demonstrated proficiency in Python, • Strong command of foundations of applied statistics, linear algebra, and time series models, • Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources, • Knowledge of financial markets, • Highly motivated, willing to take ownership of his/her work, • Collaborative mindset with strong independent research ability, • Commitment to the highest ethical standards Preferred Skills

As a Quant Investment Associate, you will be the analytical engine behind our Fixed Income platform. You will not only build the models but also interpret the data to provide strategic recommendations on portfolio construction, tactical asset allocation, and risk-adjusted optimization. This is a highly visible, front-office role where your work directly impacts the alpha generation of our Fixed Income mandates. Key Responsibilities Portfolio Construction & Optimization • Quantitative Modeling: Design and implement robust frameworks for multi-sector Fixed Income portfolio construction (including Sovereigns, Corporates, High Yield, and Securitized products)., • Optimization: Develop and refine optimization algorithms (e.g., Mean-Variance, Risk-Parity, or Factor-based) that account for transaction costs, liquidity constraints, and regulatory requirements (e.g., Basel IV/Solvency II)., • Alpha Generation: Utilize systematic signals and alternative data to identify relative value opportunities across global fixed-income markets., • Scenario Analysis: Conduct "Stress-Testing" and "What-If" simulations to quantify portfolio sensitivity to interest rate shocks, spread widening, or geopolitical events., • Custom Tooling: Build and maintain proprietary Python-based libraries for bond pricing, yield curve fitting, and attribution., • Visual Dashboards: Develop real-time dashboards (using Streamlit, Dash, or Tableau) to visualize portfolio exposures, risk concentrations, and performance drivers., • Ad-hoc Analytics: Rapidly respond to market events by performing deep-dive data analysis on specific sectors or idiosyncratic risks. Qualifications • Education: Masters or PhD in a STEM field (Financial Engineering, Mathematics, Physics, Statistics, or Computer Science)., • Experience: 3–10 years in a quantitative role within Fixed Income, ideally on the buy-side (Asset Management or Hedge Fund)., • Programming: Expert-level Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow). Experience with SQL and version control (Git) is essential., • Fixed Income Mastery: Deep understanding of duration/convexity, credit spreads, OAS, and the mechanics of structured products or derivatives (CDX, Swaps, Futures)., • Communication: Ability to bridge the gap between "Quant" and "PM"—explaining technical methodologies to non-technical stakeholders., • Commercial Acumen: A passion for markets and a drive to find profitable patterns in data., • Agility: Comfortable in a fast-paced trading floor environment where priorities can shift based on market volatility.

The Department of Biomedical Engineering - Prof. Elham Azizi's Lab, is looking for a Staff Associate III to: Functional Knowledge (35%) - Develop advanced probabilistic and causal generative frameworks linking molecular to clinical data; design interpretable representation spaces for tumor-immune dynamics and therapy response. Technical Expertise (25%) - Engineer LLM and diffusion/flow-matching pipelines; integrate multi-GPU distributed training, experiment tracking, and MLOps automation. Problem-Solving Skills (15%) - Innovate adaptive fine-tuning, multi-task learning, and agentic reasoning strategies to improve generalization and data efficiency. Decision Making/Autonomy (10%) - Lead architectural and data design decisions; prioritize experiments aligned with program milestones; evaluate trade-offs between model accuracy and interpretability. Communication Skills (10%) - Present findings at internal symposia and external conferences; co-author manuscripts; write high-quality documentation and technical reports. Mentorship/Leadership (5%) - Mentor junior engineers and research assistants; provide guidance on causal inference methods and AI-in-loop experimentation. B.S./B.E. (minimum) in Computer Science, Biomedical/Electrical Engineering, Statistics, Bioinformatics, Applied Math, or related field. MS or PhD degree is preferred but not required. Required qualifications • Substantial expertise in training deep learning models and tuning large foundation models., • Expertise with developing efficient data loaders for large datasets and optimizing training workflows., • Deep knowledge of probabilistic modelling, self-supervised learning and representation learning, diffusion/VAE/flow matching architectures, • Strong Python, PyTorch/JAX, containerization & MLOps skills; familiarity with distributed training and modern experiment-tracking stacks, • Experience with AI coding tools (e.g., Copilot, Cursor) Preferred extras • M.S. or graduate-level degree in relevant field, • Experience with single-cell and spatial genomic or imaging data, and multimodal integration, • Expertise in statistical causal discovery and inference, • Publications or open-source contributions in generative models, • Strong interest in applications and driving impact in cancer biology and immunology 6+ years of experience in software engineering including: 3+ yrs hands-on experience training generative AI or large-language models at scale 2+ years experience with statistical or generative modeling Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

The Department of Applied Physics and Applied Mathematics at Columbia University invites applications for an Associate Research Scientist position in theoretical condensed matter and materials physics, with an emphasis on the development of computational and analytical methods for strongly correlated electron systems. This position is part of a research program dedicated to advancing the Variational Discrete Action Theory (VDAT) - a novel variational approach to the quantum many-body problem. Candidates should have a strong background in theoretical/computational condensed matter and or materials physics, or related field. Experience with computational many-body physics is desired, including techniques such as the dynamical mean-field theory, quantum Monte-Carlo approaches, diagonalization approaches, etc. Strong candidates with related, but different, expertise will be considered. Programming experience is desirable. Strong communication skills (oral and written) are essential, and the ability to mentor students in a team environment is desirable. The position is initially for six months, possibly extending to four years. The position is available immediately and will remain open until it is filled. T Candidates must have a PhD in physics, materials science, applied math, chemistry, or a related field with a minimum of 2 years of relevant post-PhD experience. Columbia University is an Equal Opportunity Employer / Disability / Veteran Pay Transparency Disclosure The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.

Title: Math Adjunct Department: Mathematical Sciences Reports To: Chair Position Type: Faculty Position Summary: The Department has part-time adjunct positions available particularly for courses such as Pre-Calculus, Calculus, Differential Equations, and Statistics & Probability. Essential Functions: Functions include, but are not limited to, teaching assigned course(s), maintaining student attendance records, and holding regularly scheduled office hours. Additional Functions: If assigned to a coordinated course, must participate in common exam proctoring and grading. Essential Characteristics: Must abide by the university's core values which include excellence, integrity, civility, social responsibility, diversity and communication. Prerequisite Qualifications: M.S. degree in Mathematics or Statistics or related field required. Preferred Qualifications: PhD preferred. Prior teaching experience strongly preferred. Prior teaching experience at the collegiate level is a plus. At the university's discretion, the education and experience prerequisites may be excepted where the candidate can demonstrate to the satisfaction of the university and the SPHS Leadership Council, an equivalent combination of education and experience specifically preparing the candidate for success in the position. Bargaining Unit: AFT-UCAN Salary Information: In compliance with the NJ Pay Transparency Law, the rate for this position is $2668 per contact hour (USD). NJIT considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses or other items. FLSA: Exempt Part-Time Special Instructions to Applicants: Must have CV/Resume and cover letter attached. If available, please provide teaching evaluations with CV and cover letter using the "other documents" option to attach. Apply NowShare Save Job

Job DescriptionContractRemoteRole DescriptionFast-growing AI data services company and subsidiary of, is seeking mathematicians to join our AI training project. In this role, you will review AI-generated responses, evaluate the reasoning quality and step-by-step problem-solving, and provide expert feedback that helps models produce answers that are accurate, logical, and clearly explained. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in calculations, methodology, or conceptual understanding; fact-check quantitative information across; write high-quality mathematical explanations and model solutions that demonstrate correct methods; and rate and compare multiple AI responses based on mathematical correctness and reasoning quality.Your Profile • You hold a MS or PhD in Math/Stats or a related field in one of the top 100 universities., • Confident in pure and applied mathematics, proofs, modeling, statistics/probability, and optimization., • Expert at fact-checking information using public sources across multiple domains., • You communicate mathematics clearly and turn advanced theory into real-world solutions., • Background in research, analytical writing, debate, programming, or mathematics is preferred., • English proficiency C1 and above with excellent writing skills., • For PhD holderss: you have developed or critically reviewed complex math content (e.g., problem banks, proofs, textbook sections, research notes)., • Bonus: Data labeling, RLHF, or AI model evaluation experience.Key Responsibilities, • Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects., • Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance., • Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.

Job Description Company: Top-tier hedge fund with an MFT-focused team, offering a collaborative, research-driven environment. Emphasizes machine learning for cutting-edge strategy development.Overview: ML Quant Research opportunity with a collaborative PhD heavy team. Will be using ML like LLMs and Nonstationarity modeling to develop forecasting and alpha strategies for equities trading team. This is a collaborative model with 5 years+ average tenure on most of the team (not a pod shop). Key Responsibilities: • Design and implement machine learning alpha research models and forecasting models for a mix of intraday and longer hold MFT equities strategies., • Utilize LLMs, generative models, and nonstationarity modeling to develop effective and profitable trading signals and strategiesQualifications:, • 3-7 years of experience in a Quant Research, • Experience at a top buy side firm, or equivalent experience, • Practical use of ML models in production., • PhD level Math/Statistics skills, • Collaborative and patient nature #LI-NB1

Job Description Company: Top-tier hedge fund with an MFT-focused team, offering a collaborative, research-driven environment. Emphasizes machine learning for cutting-edge strategy development.Overview: ML Quant Research opportunity with a collaborative PhD heavy team. Will be using ML like LLMs and Nonstationarity modeling to develop forecasting and alpha strategies for equities trading team. This is a collaborative model with 5 years+ average tenure on most of the team (not a pod shop). Key Responsibilities: • Design and implement machine learning alpha research models and forecasting models for a mix of intraday and longer hold MFT equities strategies., • Utilize LLMs, generative models, and nonstationarity modeling to develop effective and profitable trading signals and strategiesQualifications:, • 3-7 years of experience in a Quant Research, • Experience at a top buy side firm, or equivalent experience, • Practical use of ML models in production., • PhD level Math/Statistics skills, • Collaborative and patient nature #LI-NB1

Job DescriptionAbout CookUnity: Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul. Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world. If that mission has you hungry in more ways than one, you've found the right job posting. About the Role We're hiring for an experienced ML-focused Data Scientist to own growth-oriented modeling across the customer lifecycle - acquisition, activation, retention, resurrection and monetization. You'll work alongside other data scientist to design, validate, and productionize statistical and ML systems (pLTV, churn/survival, uplift/incrementality, lookalikes, clustering/embeddings, NBA/ranking) that directly drive growth. This is a hands-on role for someone with strong mathematical/statistical foundations, broad modeling experience, and pragmatic MLOps chops who can lead experiments and partner closely with Marketing, Engineering, CRM, and Product. What you'll do… • Lifecycle modeling: Build and maintain predictive LTV, churn (including survival/time-to-event), order-rate, and resurrection models that feed acquisition, CRM, and retention strategies., • Acquisition & lookalikes: Create lookalike / propensity models for paid channels and audience construction; optimize CAC vs LTV tradeoffs., • Next-Best-Action & personalization: Develop NBA/ranking models, small-scale recommenders and embedding-based similarity systems to increase activation and orders., • Unsupervised & representation learning: Lead segmentation, clustering, embeddings and representation work that create actionable cohorts and features., • Production & MLOps: Own the full model lifecycle - training pipelines, CI/CD, model registries, containerized deployment, monitoring, retraining and drift detection; partner with engineers to operationalize models into CRM, marketplace and paid channels., • Model governance & reproducibility: Ensure models are well-tested, explainable, calibrated, and auditable; document assumptions, limitations and business mappings., • Cross-functional influence: Translate technical work into product recommendations, dashboards and clear narratives for Growth, Marketing and Engineering. Mentor peers and raise modeling and MLOps standards.Required qualifications, • 5-8+ years in data science, applied ML or statistics, with a track record of shipping production models., • Strong math & statistics: probability, inference, regression, survival analysis/time-to-event, causal reasoning, and familiarity with statistical modeling tradeoffs., • End-to-end ML experience: experience building, validating and deploying classification/regression/ensemble/deep models; comfort with embeddings and representation learning., • MLOps & production skills: pragmatic experience with model CI/CD, model registries (MLFlow or similar), containerization (Docker), orchestration (Airflow), and runtime infra (K8s / ECS)., • Software engineering & tooling: Python (pandas, scikit-learn, XGBoost/LightGBM, PyTorch/TensorFlow optional), strong code hygiene, testing and reproducibility., • Product & stakeholder collaboration: excellent communication, ability to embed with Growth/CRM/Marketing and translate models into product decisions., • Education: BS in a quantitative field required; MS/PhD in statistics, math, CS, economics or similar preferred.Nice-to-haves, • Experience in subscription marketplaces, food-tech, or consumer marketplaces., • Familiarity with feature stores, Snowflake/BigQuery, and production monitoring tools., • Experience with causal libraries (EconML), uplift frameworks, or survival modeling packages., • Prior work on small-scale recommender systems, embeddings, or NLP personalization. Learn More About CookUnity We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale. We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect! Benefits 🩺 Health Insurance coverage 🌅 401k Plan ⛱ Unlimited PTO 🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical 🐣 Paid Family leave 🕯 Compassionate Leave: 3-5 days each time the need arises 🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly 🧘🏽️‍♀️ Wellness perks: access to a nutritional coach and fitness subsidies to build a healthy lifestyle 👩🏾️‍🏫 Personalized Spanish coach 🌟 Awesome opportunity to join a company that is looking to change how we eat and how chefs work! Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.Pay Range for this position$160,000—$185,000 USD If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time! CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability. A quick note for all candidates We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us: • Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com, • Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page., • We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.

Job Description Quant Developer/Market Maker The Company - Our client is a small trading shop, whose founders have an extremely successful track records in all prior ventures in high Frequency trading. The core consists of small group of educated PhD scientists who came together to build trading models in multiple asset classes over the last decade. They were first challenged to finding non-random behavior in data sets as they tackled the FX market with new algorithmic trading and quickly separated themselves from everyone else in the market. That company was bought by a world leader in capital markets, and they moved into equities, and were successful as a prop trading shop for over 6 years, and was eventually bought as well. They are now onto their next venture they are looking to tackle the cryptocurrency market. As a trusted asset to every large financial trading desk through the years, institutions have expressed great interest in trading with them, and the firm provides crypto asset execution, trading, and advisory services to institutional clients, as well as making markets on various exchanges, as well as providing customized algorithms to split up trades. They are looking for a Quant Developer (Quant/Market maker) to join this team, and head up building the market making product. This person does not need crypto experience, but needs to understand the technical backbone of market making systems, market microstructure and the technical needs for setting up and monitoring strategies. All systems are built from scratch and brand new. The competitive advantage is the model and brilliant combination of quantitative minds. They build their systems to be smarter, highly risk averse, rigorously tested and with a strict scientific approach to modeling. The Role – Starting as an Senior Quant Developer/Market Maker you will get a chance to get in on the ground floor in a low key environment and let data drive your decisions. This opportunity is for a top notch engineer with strong quantitative skills, to take a pragmatic approach and enjoy the flexibility of building something, in an environment where there is no red tape, or barriers to your creativity. It is a great opportunity for a Quant who wants to leverage technical/math skills to learn more about, and get into trading. Ideas for strategies are encouraged, and team will help you test and implement them. This is an opportunity for you to work with elite minds as well as trade ideas, grow in knowledge and gain exponential earnings potential. The overall climate is for everyone to make money and go home satisfied. Flexible hours and telecommuting is offered. Qualifications ¬ Experience working with high performance trading systems, specifically market making systems. ¬ FX is preferred over equity, because it translates better to the crypto-market. ¬ Strong Java/C# Programming ¬ Ability to develop systematic models from a mathematical approach ¬ Strong Math/Quantitative Skills and experience with Large Data Sets ¬ Top Tier Education – Masters or PhD (Math, Science, Computer Science, Engineering, Computational Finance) Skills and abilities you will be finely rewarded, compensation greatly depends on experience, equity and salary will be based on value.

Job DescriptionDescription: Emergence AI is building next-generation agentic AI systems that move beyond code generation to provable task completion, verification, and long-horizon autonomy. We’re looking for exceptional MS and PhD students to join us for a high-impact summer research internship. What you’ll work on • Design and prototype agentic systems for complex, long-horizon tasks (data pipelines, simulations, scientific workflows)., • Explore formal specifications, verification, and evaluation for autonomous agents., • Build and benchmark systems involving LLMs, planners, memory, and tool orchestration., • Apply agentic methods to accelerated science, simulations, or enterprise-scale data problems., • MS or PhD student in CS, AI/ML, Systems, Applied Math, or a related field., • Strong foundations in at least one of: AI/ML, distributed systems, programming languages, formal methods, or scientific computing., • Comfortable turning abstract ideas into working systems., • Work on real Enterprise problems at the frontier of agentic AI., • High ownership and direct exposure to research and product.

Job DescriptionQuantitative leadership position supporting the warehouse lending & asset backed credit modeling and analytics team for large US investment bank Responsibilities: • Lead the credit loss modeling coverage for structured / asset-based lending portfolio, for both stress test and CECL., • Develop, and maintain the performance of Credit Risk and Stress Testing models for the lending portfolio with broader credit analytics coverage as needed, • Participate in research, development, and implementation of credit risk models, • Provide econometric analyses to support methodology development, • Perform back-tests, stress-tests, scenario analyses and sensitivity studies, • Develop data analyses for various purposes, • Oversee work of analysts and participate in recruitment, training and development of junior members of the team. Requirements: • Broad experience in a quantitative research group at a commercial bank, investment bank, or consulting firm, • Advanced statistical skills especially in hypothesis testing, regression, and discriminant analyses, • A thorough knowledge of statistics and an internal drive to challenge and improve models with quantitative methods, • Familiarity with statistical packages (e.g., MATLAB, or R ), • Team player with strong interpersonal and communication skills, • Advanced degree (PhD or MS) in a quantitative discipline (e.g., statistics, physics, math) For immediate consideration, please forward resume and contact details to: Ashton Lane Group is a boutique executive recruitment firm serving the Banking, Insurance, and Alternative Investment sectors. For the latest opportunities, visit Ashton Lane Group® “A trusted advisor throughout your career”

Job Description Position Description: A client of AlphaStaffHCM is looking for a Software Engineer with deep expertise in Mathematical Optimization and algorithm development. This role is critical in architecting the core software engine that drives our proprietary photonic quantum processors, combining complex mathematical formulations with physical optical hardware feedback. Responsibilities • Design and implement the high-performance C++ runtime and Hardware Abstraction Layer (HAL) for photonic optimization computers., • Profile and optimize critical execution paths to minimize latency, addressing bottlenecks in memory bandwidth, cache locality, and data transfer., • Collaborate with FPGA, Electrical engineers and Firmware engineers to ensure to create, test, and optimize device interfaces., • Develop algorithmic enhancements to usage of quantum feedback to solve NP hard optimization problems more efficiently with higher solution quality., • Write efficient, thread-safe code for concurrent hardware control and real-time signal processing., • Design and implement novel algorithms that map optimization and machine-learning problems onto entropy-based photonic quantum processors, including post-processing pipelines., • Build software layers to decompose and orchestrate large-scale optimization problems across multiple photonic hardware resources. Required Qualifications • 6+ years of experience in software engineering with a focus on systems or HPC., • Strong proficiency in C++ and Python, • Strong mathematical background in Convex Optimization, Quadratic Programming (QP), Mixed-Integer Linear Programming (MILP), or Gradient-Free Methods., • Experience with Numerical Analysis and high-performance math libraries (e.g., BLAS, LAPACK, Eigen)., • Familiarity with protocols (e.g., UART, SPI, gRPC, REST) and software integration., • Strong understanding of performance tuning, memory management, and fault-tolerant design., • Familiarity with Linux system programming and build toolchains (CMake, GCC/Clang)., • Experience working in cross-functional teams involving hardware, physics, and software. Preferred Qualifications • Advanced degree (MS/PhD) in Computer Science, Physics, or Mathematics., • Experience with classical optimization solvers (e.g., CPLEX, Gurobi) or heuristic frameworks., • Familiarity with Open Quantum Systems or optical feedback mechanisms., • Background in Digital Signal Processing (DSP) or control theory., • Knowledge of containerized deployment using Docker. Skills C++, High Performance Computing (HPC), Algorithm Design, Mathematical Optimization,, Multi-threading, Linux, CMake, Python, Performance Profiling, Hardware Abstraction, Signal Processing. Disclaimers: AlphaStaff, Inc. and the Client are equal employment opportunity employers and do not discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, past or present military service, disability, genetic information, or any other basis protected by applicable federal, state, or local laws.

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Delivering with Uber is an alternative to a part-time or full-time job and can get you earning cash quickly.Delivering with Uber allows you to earn quick cash while maintaining the flexibility your schedule requires (gig, part-time, full-time, seasonal, hourly, or temporary).With Uber, you can cash

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Delivering with Uber is an alternative to a part-time or full-time job and can get you earning cash quickly.Delivering with Uber allows you to earn quick cash while maintaining the flexibility your schedule requires (gig, part-time, full-time, seasonal, hourly, or temporary).With Uber, you can cash

Delivering with Uber is an alternative to a part-time or full-time job and can get you earning cash quickly.Delivering with Uber allows you to earn quick cash while maintaining the flexibility your schedule requires (gig, part-time, full-time, seasonal, hourly, or temporary).With Uber, you can cash

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