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Job DescriptionBenefits: • 401(k), • Dental insurance, • Health insurance, • Paid time off Responsibilities: Task A Data Collection & Quantitative Analysis • Utilize publicly available data sources (e.g., Census, USDOT, BLS, FRED) to collect economic, demographic, and transportation data., • Organize and present data in Excel for knowledge transfer and clarity., • Identify trends in economic, demographic, and transportation data to inform analyses such as inflation analysis and remote work trends., • Contextualize results using comparable analyses or data sources., • Develop metrics to highlight trends in transportation and economic issues., • Automate data extraction using programming languages like Python or R.Task B Research & Reporting, • Conduct qualitative and quantitative research to examine market and industry behavior., • Perform literature reviews and communicate findings effectively., • Monitor and provide commentary on economic releases., • Review and summarize reports to guide project decisions., • Bachelors degree in Economics, Finance, Statistics, or a related field (Masters degree preferred)., • Minimum of 3 years of experience in economics, transportation, or statistical analysis., • Proficiency in Microsoft Excel, PowerPoint, Word, Access, and Power BI., • Experience with analytical tools like R, Python, EViews, or Stata., • Strong knowledge of statistics or econometrics., • Demonstrated ability to work on multiple projects independently and efficiently., • Excellent communication and collaboration skills in individual and team settings.Work Environment, • Hybrid work model with three days per week in-office at the 4 World Trade Center, NYC., • One-year anticipated assignment duration.Additional Requirements, • Candidate must obtain a SWAC I.D. with associated security clearances upon hiring., • Ability to adapt and perform a wide range of tasks in a dynamic environment. Flexible work from home options available.

Job DescriptionCompany Description Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society. The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through nineteen professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good. Job Description Columbia University School of Professional Studies seeks industry professionals for the role of adjunct Lecturer to develop and teach various courses in the school’s M.S. in Political Analytics program. The program combines politics with advanced quantitative methods to enhance data skills that will drive decision-making and communicate effectively about data and politics. The program’s curriculum can be found here. Candidates should indicate in a cover letter, areas of subject matter expertise and what type of course they would be interested in or qualified to teach. Examples of current courses taught include: • Big Data & Political Strategy, • Campaign Finance & Fundraising Analytics, • Data Science for Political Analytics Responsibilities • Lead in-person class lectures, instructional activities, and classroom discussions, • Evaluate student work and grade assignments, • Monitor student concerns and inquiries, and be the first point of contact for student questions, • Hold weekly office hours, • Prepare, maintain, and enhance the course in Canvas, Columbia University’s learning management system for onsite and online courses, • Part‐time Lecturers who are new to SPS must complete Canvas training (online learning management system), • Attend Political Analytics faculty meetings, • If assigned to design the course, responsibilities also include:, • Develop course objectives that align with program-wide learning outcomes, • Create activity maps tying course activities to objectives, ensuring industry relevance, • Draft a detailed syllabus (course description, schedule, grading rubric, and assessments) for review and approval by the Program Curriculum Committee and the Committee on Instruction (COI) Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty that have outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. Requirements • Graduate degree in an area related to political science, data science, quantitative methods or related field, • 10+ years of professional experience in a role involving political analytics, • Knowledge of statistics, econometrics, quantitative analysis or related techniques, • Knowledge and familiarity with analysis software (e.g. R), • Doctoral degree or equivalent in a relevant field, • Prior experience with electoral campaigns, policy-making initiatives, advocacy efforts, or lobbying operations, • University teaching experience, ideally at the graduate level Additional Information Compensation - $10,000 - $15,000 per semester-length course. Review of applications begins immediately and will continue until positions are filled. All applicants, please provide: • A resume/CV inclusive of university teaching experience -- highlight teaching at the graduate level, • A cover letter indicating the courses they would be interested in or qualified to teach, areas of subject matter expertise, and availability to teach in-person Columbia University is an Equal Opportunity Employer / Disability / Veteran

Job Description Job Title: Machine Learning Engineering Director Qualifications: • Hold a Bachelor's degree in a technical field (e.g., computer science, machine learning, mathematics, physics, statistics, econometrics), or equivalent hands-on experience., • Demonstrate coding proficiency in at least one programming language, with a strong preference for Python., • Possess a strong foundation in mathematics, statistics, and machine learning concepts, enabling the development, training, and evaluation of production models and facilitating the comprehension of research papers., • Showcase exceptional communication skills, facilitating the effective conveyance of technical ideas and fostering productive collaborations with business partners., • Exhibit an entrepreneurial mindset and a deep passion for unlocking the potential of Large Language Models (LLMs) and classical machine learning techniques to drive a multi-billion dollar business., • Provide evidence of successful management experience, having effectively led teams of 1-2 machine learning engineers or scientists., • Proficiency in building RESTful APIs, ideally using Flask, FastAPI, or other Python frameworks., • Experience in constructing data pipelines that underpin Machine Learning model development., • Familiarity with Python libraries for machine learning, data manipulation, and mathematics, such as PyTorch, numpy, and pandas.

Job DescriptionVoleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. We are seeking a senior researcher to lead feature engineering for predictive models. You will lead a team of researchers in applying financial insight and statistical machine-learning methods to uncover predictive signals from structured and unstructured data. Your work will directly improve model performance and investment outcomes. This is a unique opportunity to set a feature research agenda, mentor outstanding colleagues, and collaborate with best-in-class teams across research, engineering, and investment strategy. Responsibilities • Lead the design and development of features for use in supervised and unsupervised learning, drawing on a variety of econometric and financial concepts., • Translate economic and financial model constructs into scalable, empirical signal definitions, using structured and unstructured data., • Collaborate with data engineering teams to implement clean, robust pipelines for feature generation and version control across large securities universes., • Shape the experimental framework for evaluating feature performance in predictive models., • Establish and manage best practices for documenting construction logic, assumptions, and behavior of each feature under different economic and market conditions., • Manage and coach the featuring engineering team, fostering a collaborative and results-driven environment., • Align the team’s efforts with broader research and model development goals through strategic planning and cross-functional collaboration.Requirements, • Demonstrable clarity of thought., • Grit, in large quantities., • 7+ years of experience in quantitative finance, signal research, or predictive modeling, including at least 2 years leading research teams or initiatives., • Strong scientific programming skills in Python and/or R; experience with SQL or Spark is a plus., • Deep understanding of financial markets, company fundamentals, econometrics, and financial-economic models., • Extensive experience designing features for use in machine-learning pipelines or research environments (e.g., PyTorch, scikit-learn)., • Master's degree in a relevant quantitative field.Preferred, • Ph.D. in a quantitative field., • Experience managing globally distributed research or data-analysis teams.

Job DescriptionAbout Taskrabbit: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do's, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We're looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we're creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! This role is a two days a week in office, hybrid role that can sit in either our San Francisco office or our New York City office (Opening January 2026!) About the Role Data Science plays a crucial role in driving impact at Taskrabbit. As a member of the team, you will help drive our business strategy forward through predictive insights. We are seeking a highly skilled and motivated Senior Data Scientist to join us, working closely with cross-functional teams from product, engineering, marketing and operations to provide data-driven insights and solutions that enhance our products and accelerate growth. What you will work on • Be a strategic thought partner with stakeholders from product, marketing, and operations to define high-impact analytical problems, and solve them using different analytical and statistical approaches. Present actionable insights in a clear and compelling manner., • Proactively perform analytical deep dives to identify strategic growth opportunities in key business levers, e.g. customer/partner acquisition, retention, conversion, etc., • Collaborate with stakeholders to define and measure success metrics for new features and products, conduct advanced experimentation and causal inference to optimize product features and user experiences, • Foster a data-driven culture within the organization by advocating for best practices in data analysis and interpretation.Who you are, • BS, MS or Ph.D. in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research, or related field)., • A minimum of 5 years industry experience in data science; previous experience in a marketplace business is a plus, • Experience with advanced experimentation and statistical modeling, • Excellent analytical and problem-solving skills., • Excellent business acumen and strategic thinking skills, • Advanced in SQL, experienced in Python, and familiar with data pipeline tooling (e.g. dbt) and git., • A self-starter with the ability to work independently and drive your own projects end-to-end with a track record of landing strong business impact The base pay range for this position is $145,000 - $180,000. This range is representative of base pay only and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level. You'll love working here because: • Taskrabbit is a Hybrid Company. We value flexibility and choice but also stay committed to regular in-person connection., • The People. You will be surrounded by some of the most talented, supportive, smart, and kind leaders and teams -- people you can be proud to work with!, • The Diverse Culture. We believe that we make better decisions when our workforce reflects the diversity of the communities in which we operate. Women make up half of our leadership team and our diversity representation is above that of the tech industry average. Taskrabbit is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, ancestry, citizenship, sex, gender, gender identity, sexual orientation, age, marital status, military/veteran status, or disability status. Taskrabbit is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Taskrabbit will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. Taskrabbit will never use text or chat applications to conduct interviews. We have a thoughtful and interactive interview process that includes an initial recruiter phone screen and several video-based interviews with our hiring teams. Communications will always be conducted by taskrabbit.com domain names.

Job DescriptionCompStak is a pioneer in crowdsourced commercial real estate (CRE) data and analytics. Our platform transforms raw lease, sales, and property data into actionable insights for brokers, lenders, landlords, and investors. As we expand our data products, the scale and sophistication of our data pipelines and analytical systems are critical to delivering reliable, timely, and high-quality insights to our customers. Location: New York, NY (Hybrid- Three days per week in the office, subject to change) We are seeking a Quantitative Researcher – Real Estate & Econometrics with a strong foundation in economics, econometrics, finance, or commercial real estate and an interest in applying quantitative modeling to real-world market behavior. This role is ideal for someone who understands how markets work, has experience working with data, and wants to apply (and grow) modern analytical and data science methods within a commercial real estate context. In this role, you will help shape how CompStak analyzes, models, and interprets market dynamics by combining domain expertise with econometric and quantitative techniques. Your mission is to:-Apply econometric and statistical modeling to analyze and forecast trends in commercial real estate and related economic drivers.-Learn and apply modern analytical and machine learning techniques as needed to enhance insights and support CompStak’s data products.-Build scalable workflows that integrate structured CRE datasets with new, unstructured sources to support data enrichment and automation.-Collaborate closely with engineering, product, and data teams to develop data-driven solutions.-Bridge domain knowledge and quantitative methods to deliver models that are accurate, interpretable, and meaningful for business decisions.Responsibilities • Develop econometric and predictive models: Use quantitative methods to identify patterns, forecast trends, and interpret economic relationships in CRE markets., • Build and optimize data workflows: Create and refine data ingestion and transformation pipelines for structured and unstructured commercial real estate datasets., • Ensure data quality: Clean, validate, and reconcile datasets from diverse sources to ensure accuracy and reliability., • Communicate insights: Translate complex quantitative analysis into clear, actionable insights for both technical and non-technical stakeholders., • Stay current: Keep up with developments in econometrics, applied analytics, and trends in CRE markets and data science.Skills & Experience, • 3+ years of experience in an econometrics-focused or analytical role (e.g., economics research, finance, market analysis, consulting, commercial real estate, or corporate strategy)., • Strong understanding of econometrics, applied statistics, and quantitative modeling, demonstrated through academic or professional experience., • Proficiency in Python and familiarity with analytical/ML libraries (pandas, NumPy, scikit-learn, XGBoost)., • Experience working with large or complex datasets and using data to study market dynamics., • Excellent organizational, communication, and stakeholder management skills., • Bonus: Hands-on experience or interest in LLMs, embeddings, NLP tools, or modern ML frameworks (e.g., Hugging Face, LangChain, PyTorch/TensorFlow).

Job Description About Overdeck Family Foundation Overdeck Family Foundation (“the Foundation”) was founded in 2011 to provide all children the opportunity to unlock their potential. The Foundation focuses on enhancing education through funding efforts in early childhood, hands-on STEM education, and K-9 programs, supporting both educators and student-centered learning environments. Our grantmaking and strategic support focus on unlocking innovation, evidence, and growth opportunities to accelerate key academic and socioemotional outcomes for all children. At Overdeck Family Foundation, we achieve our impact by collaborating with rigor, fostering a culture of curiosity and learning, and living our core values to drive meaningful change. Visit for more information on our foundation, including our research repository. The Research Fellow Position Overdeck Family Foundation is seeking a Research Fellow to work with the Research & Impact Officer, Meghan McCormick, to support the Foundation’s evidence and research efforts. This role will contribute to activities including evidence reviews for prospective grantees, evidence summaries for funding recommendations, and targeted communication activities such as updating summaries of research funded by the Foundation. The position is ideally suited for advanced doctoral students or post-doctoral researchers in economics, public policy, sociology, applied psychology, or education, particularly those with expertise in econometrics and K-12 education. What You’ll Help Us Do: * Conduct evidence reviews to assess potential grantee organizations against the Foundation’s goals and priorities. * Develop evidence summaries to support funding recommendations and presentations. * Collaborate on updating and maintaining a repository of research studies funded by the Foundation. * Support communications activities by creating clear, concise summaries of research findings. Who You Are: You are outcomes-driven. You are motivated by the Foundation’s mission to open doors for every child in the U.S. by measurably enhancing education both inside and outside the classroom. You bring expertise in quantitative research. You have advanced training in research methodology (ex: experimental and quasi-experimental designs), knowledge of the federal ESSA evidence tiers, and experience conducting independent research. You communicate effectively. Your ability to synthesize and clearly present complex research findings ensures your work drives understanding and decision-making. You are independent and proactive. You excel at managing your tasks and producing high-quality outputs with minimal supervision. You value collaboration. You’re a team player, open to feedback, and eager to work with internal colleagues to enhance the Foundation’s learning and impact. What You’ve Done: * Advanced doctoral coursework or a post-doctoral position in a relevant field. * Expertise in econometrics, quantitative research methods, and K-12 education preferred. * Strong written and verbal communication skills. * Demonstrated ability to work independently and meet project deadlines. Working at Overdeck Family Foundation This fellowship opportunity will span from March to October 2025, with an estimated time commitment of 35-40 hours per month. Overdeck Family Foundation will offer the Research Fellow a competitive monthly retainer of $2,500, totaling $20,000 for the full engagement. The role is fully remote though the Fellow will be welcome to join select meetings with the team in person at the Foundation’s New York City offices based on geographic proximity. The Research Fellow may perform duties as convenient though would be expected to be available to join occasional meetings or check-ins during the Foundation’s core working hours (10 a.m. to 4 p.m. ET). How to Apply Please complete the application form, which includes uploading the following materials: * Resume/CV * Example of Original Research: Submit an original research paper that you have led or co-led. This can be a working paper or a published paper. * Example of a Literature Review: Share a literature review that you have led. This can be either published or unpublished.

Job DescriptionSamba TV tracks streaming and broadcast video across the world with our proprietary data and technology. We are on a mission to fundamentally transform the viewing experience for everyone. Our data enables media companies to connect with audiences for new shows and movies, and enables advertisers to engage viewers and measure reach across all their devices. We have an amazing story with a unique perspective on culture formed by a global footprint of data and AI-driven insights. Reporting to the VP of Data Science, as the Senior Data Scientist on our Measurement Sciences team, you will design and operationalize robust measurement frameworks—leveraging causal inference, experiment design, and advanced machine learning—to deliver transparent, actionable insights on ad incrementality, audience targeting, and cross-platform attribution. You will provide thought leadership and help guide the transformation of how advertisers measure, attribute, and optimize TV campaigns across linear and streaming platforms.WHAT YOU'LL DO • Design and implement ad incrementality measurement methodologies (A/B tests, uplift modeling, synthetic controls, Bayesian causal models) for linear TV and Connected TV (CTV) campaigns, • Develop globally scalable audience segmentation and targeting models using our viewership data ecosystem via millions of connected TVs, • Build and validate multi-touch attribution frameworks that reconcile impressions, views, and conversions across linear, CTV, OTT, and digital channels, • Lead the full analytics lifecycle—from data ingestion/ETL (SQL, Spark, Python) through feature engineering, model development, evaluation, and production deployment, • Partner closely with data engineering and DevOps teams to operationalize models in our cloud platform and ensure data quality, security, and scalability, • Translate complex analytical findings into clear, concise presentations and dashboards for internal stakeholders and external clients, driving strategic decision-making., • Support sales and marketing teams with the development of strong positioning stories to highlight the value of our audience media and measurement opportunities, • Mentor junior data scientists and analytics engineers, fostering best practices in experimentation, code quality, and reproducibility WHO YOU ARE, • Have a Master’s or advanced degree in Statistics, Econometrics, Data Science, Computer Science, or related quantitative field, • 7-10 years of hands-on experience in advertising/marketing analytics, media measurement, or a closely related discipline, • Expert in causal inference techniques (RCT design, difference-in-differences, propensity scoring, synthetic control) and uplift modeling. Background in Bayesian statistics or hierarchical modeling for uncertainty quantification, • Have a proven track record building attribution and incrementality solutions for TV and cross-media campaigns, • Have advanced programming skills in Python and SQL; Familiarity with Spark or other distributed compute frameworks, • Have demonstrated leadership in mentoring small data science teams and managing end-to-end data science projects, • Able to visualize data in a way that makes it easy for others to understand, • Are detail-oriented, highly organized, and proactive, • Have strong verbal and written communication skills, with the ability to explain complex analyses to both technical and non-technical audiences, • Thrive in a dynamic, fast-paced Agile and global environment, and being a team player, • Experience with data platforms (Databricks, Sagemaker, BigQuery, etc.), data orchestration tools (Airflow, dbt) and CI/CD best practices a plus, • Bonus: Strong knowledge or experience working with TV viewership data sources (set-top box, return-path, panel, census-level) and measurement vendors (Samba TV, Nielsen, Comscore, etc.)

Job Description ABOUT US | HR&A Advisors, Inc. (HR&A) is an employee-owned company advising public, private, non-profit, and philanthropic clients on how to increase opportunity and advance quality of life in cities. We believe in creating vital places, building equitable and resilient communities, and improving people’s lives. From Brooklyn to London, Medellin to Hong Kong, we have guided hundreds of clients in transforming real estate and economic development concepts, and public infrastructure, first into actionable plans and then into job-producing, community-strengthening assets. Our clients include real estate owners and investors, hospitals and universities, cultural institutions and philanthropies, community development organizations, and governments. HR&A has offices in Atlanta, Dallas, Los Angeles, New York, Raleigh, Washington D.C. and the Bay Area. We come from diverse backgrounds, have a breadth of lived experience, and share a passion for cities. We are former city officials, executive directors, planners, lawyers, architects, and economists. Hear more about the HR&A experience from our staff. Learn more about careers at HR&A on our website here. THE ROLE | HR&A’s is seeking a full-time Analyst, Real Estate based in our offices in New York, Los Angeles, or the Bay Area. Our analytical staff form the foundation of our team-oriented and collaborative structure and help to drive our data-driven approach to city building. Analysts are early career professionals with 2-4 years of professional experience and draft the substance of our client work products. Depending on the project, Analysts may expect their work to include: * Real estate and housing market analysis and research * Preparation of real estate pro formas for both market rate and affordable development * Demographic data analysis * Statistical analysis and econometrics * Infrastructure funding and financing strategies * Fiscal and economic impact modeling * Case study research * Public policy and regulation review and analysis * GIS mapping Analysts also help prepare written reports, presentations in PowerPoint, and Excel models for clients, as well as firm marketing materials and proposals for new projects. EXPERIENCE REQUIRED | We are looking for candidates with strong quantitative and qualitative skills, a passion for urban development, and a deep curiosity about the challenges and opportunities facing cities today. Ideal Analysts will bring a demonstrated capacity for active project team participation, leadership, critical thinking, creativity, and other capabilities aligned with the roles and responsibilities described above, including: * 2-4 years of experience in real estate finance, urban planning or development, economics, public administration, or a similar field * Excellent written and verbal communication skills * Proficiency with PowerPoint, Excel, Word, and common AI tools (i.e. LLMs like ChatGPT) * Understanding of best practices for responsible use, citation and incorporation of AI outputs into research and other tasks, and demonstrated ability to independently verify data and AI outputs * Ability to work on multiple assignments at once * Candidates should be highly motivated independent thinkers who are detail-oriented, entrepreneurial, and sufficiently poised for client interaction. * Bachelor’s degree in a related field such as Real Estate, Finance, Urban Planning, Economics, Statistics, or Public Policy * Master’s degree in Real Estate Development (MRED), Business Administration (MBA), Urban Planning, Economics, or a related field is preferred. HYBRID WORK POLICY | HR&A fosters a collaborative and flexible work environment through our hybrid work policy. Employees work from the office at least three days a week, which allows individuals the freedom to balance their professional and personal lives while maintaining a strong connection to their teams. COMPENSATION | The base salary range for this position is $83,200 - $95,700, plus the opportunity for a discretionary year-end bonus. Where an offer falls inside this pay range is dependent on experience. We offer competitive compensation packages, based on qualifications and experience. We are an employee-owned company, meaning you will have the opportunity to benefit from the firm’s growth over time through participation in our Employee Stock Ownership Plan. Each year, the firm will contribute funds to this long-term wealth-building account and may make contributions to other retirement accounts. We also provide a comprehensive benefits package that goes well beyond coverage of 90-95% of healthcare premiums, including dental and vision coverage. HOW TO APPLY | HR&A is committed to attracting and retaining a talented, diverse, competitive team of professionals dedicated to solving the challenges of urban life. Women, people of color, members of the LGBTQ community, individuals with disabilities, and veterans are strongly encouraged to apply. To apply, click here. Please submit your cover letter and your resume as a single PDF document. Applications without this requested cover letter will not be reviewed. As part of our ongoing work to build a hiring system that mitigates bias and is based on candidate merit and performance, we ask that you submit a version of your resume and resume that has your school information removed. Please list your degree, e.g., B.A. Economics; however, remove all references to undergraduate and graduate schools you have attended. All qualified candidates will receive consideration for employment without regard to their race, religion, ancestry, national origin, sex, sexual orientation, gender identity or expression, age, disability, marital status, medical condition, veteran status or any other basis as protected by federal, state, or local law. For more information, please contact us at . Powered by JazzHR htZCMWIuUX

Job DescriptionCompStak is a pioneer in crowdsourced commercial real estate (CRE) data and analytics. Our platform transforms raw lease, sales, and property data into actionable insights for brokers, lenders, landlords, and investors. As we expand our data products, the scale and sophistication of our data pipelines and analytical systems are critical to delivering reliable, timely, and high-quality insights to our customers. Location: New York, NY (Hybrid- Three days per week in the office, subject to change) We are seeking an Applied Data Scientist – Econometrics with a strong foundation in economics, econometrics, finance, or commercial real estate and an interest in applying quantitative modeling to real-world market behavior. This role is ideal for someone who understands how markets work, has experience working with data, and wants to apply (and grow) modern analytical and data science methods within a commercial real estate context.In this role, you will help shape how CompStak analyzes, models, and interprets market dynamics by combining domain expertise with econometric and quantitative techniques. Your mission is to:-Apply econometric and statistical modeling to analyze and forecast trends in commercial real estate and related economic drivers.-Learn and apply modern analytical and machine learning techniques as needed to enhance insights and support CompStak’s data products.-Build scalable workflows that integrate structured CRE datasets with new, unstructured sources to support data enrichment and automation.-Collaborate closely with engineering, product, and data teams to develop data-driven solutions.-Bridge domain knowledge and quantitative methods to deliver models that are accurate, interpretable, and meaningful for business decisions.Responsibilities • Develop econometric and predictive models: Use quantitative methods to identify patterns, forecast trends, and interpret economic relationships in CRE markets., • Build and optimize data workflows: Create and refine data ingestion and transformation pipelines for structured and unstructured commercial real estate datasets., • Ensure data quality: Clean, validate, and reconcile datasets from diverse sources to ensure accuracy and reliability., • Communicate insights: Translate complex quantitative analysis into clear, actionable insights for both technical and non-technical stakeholders., • Stay current: Keep up with developments in econometrics, applied analytics, and trends in CRE markets and data science.Skills & Experience, • 3+ years of experience in an econometrics-focused or analytical role (e.g., economics research, finance, market analysis, consulting, commercial real estate, or corporate strategy)., • Strong understanding of econometrics, applied statistics, and quantitative modeling, demonstrated through academic or professional experience., • Proficiency in Python and familiarity with analytical/ML libraries (pandas, NumPy, scikit-learn, XGBoost)., • Experience working with large or complex datasets and using data to study market dynamics., • Excellent organizational, communication, and stakeholder management skills., • Bonus: Hands-on experience or interest in LLMs, embeddings, NLP tools, or modern ML frameworks (e.g., Hugging Face, LangChain, PyTorch/TensorFlow).