Data Scientist (Forecasting)
hace 15 horas
Valladolid
INSUD PHARMA operates across the entire pharmaceutical value chain, providing specialized knowledge and experience in scientific research, development, manufacturing, sales, and marketing of a wide range of active pharmaceutical ingredients (API), finished dosage forms (FDF), and branded pharmaceutical products, adding value to human and animal health. The activities of INSUD PHARMA are organized into three synergistic business areas: Industrial (Chemo), Branded (Exeltis), and Biotech (mAbxience), with over 9,000 professionals in more than 50 countries, 20 state-of-the-art facilities, 15 specialized R&D centers, 12 commercial offices, and more than 35 pharmaceutical subsidiaries, serving 1,150 customers in 96 countries worldwide. INSUD PHARMA believes in innovation and sustainable development. Ready to be a #Challenger? What are we looking for? We are the Data Science team within AI Labs, the applied AI department at Insud Pharma. We are a team of 30 professionals (AI Engineers, Data Scientists, DevOps Engineers, and Product Managers) working across the full breadth of the company, building products, models, and analytical solutions that directly inform and shape decision-making. We are looking for an Applied Data Scientist with strong technical foundations who is eager to work across diverse and complex problem domains (R&D, drug manufacturing process optimization, clinical trials, and beyond). You will model problems from the ground up—defining the right framing, selecting appropriate methodologies, and owning solutions through rigorous development to full deployment. We are seeking someone curious enough to tackle varied challenges (graph theory, embeddings, neural network forecasting models, causality, Bayesian optimization), rigorous enough to justify every technical and methodological decision, and independent enough to deliver end-to-end impact while taking full ownership of their work. How the team works: AI Labs operates with a startup mindset within Insud Pharma. The department is young, and the culture reflects that: flat, collaborative, and fast-moving. Beyond the Data Science team, you will work alongside AI Engineers, DevOps Engineers, and Product Managers who are equally committed to delivering high-quality work. We hold regular demo days where teams present their work, as well as whiteboard sessions where we tackle problems together. The cross-disciplinary dynamic is genuinely strong. The office is located in central Madrid (Chamberí, near Eloy Gonzalo), well connected and situated in a vibrant part of the city. The challenge! Collaborate with small, cross-functional teams. Each project is run by a small group — typically a Product Manager, a Data Scientist, an Engineer, and key stakeholders. Iteration is fast, feedback loops are short, and your contribution is visible from day one. Conduct exploratory data analysis to uncover patterns and insights in large datasets. Design, implement, and validate machine learning models and statistical methodologies to solve high-impact, real-world business problems. Translate technical findings into clear narratives, visualizations, and decision frameworks for both technical and non-technical stakeholders, enabling informed and data-driven decisions. What do you need? Strong understanding of statistics, machine learning, and data mining techniques. Expertise in Python programming, including proficiency with data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow…). Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Proven ability to translate complex technical concepts into clear, actionable insights for non-technical audiences. Knowledge and experience in causal inference methodologies will be highly valued. Knowledge of deep learning architectures and natural language processing is beneficial. Familiarity with Large Language Models (LLMs) and their applications in business contexts is a plus. Experience with version control systems (e.g., Git) and collaborative development practices. Clean, maintainable code and familiarity with software engineering best practices. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services. Experience with big data technologies (e.g., Spark, Hadoop) and SQL databases is a plus. Proficient in Spanish and English in written and verbal communication. ⏰ Flexible start time from Monday to Friday Permanent contract. doValue S.p.A. is the leading operator in Southern Europe in credit management and real estate services for banks and investors. With a unique positioning in the sector able to offer investor clients access to the markets with the highest potential in Europe. The group manages loans and real estate while operating across the NPLs management range at the level of strategy development, decision making and support services, in collaboration with a network of international consulting firms, real estate appraisers, brokers and lawyers. The Group has over 3.000 employees and an integrated range of five areas of activity: Servicing of performing and early arrears loans. Servicing of UTP loans (unlikely-to-pay). Servicing of NPL loans (non-performing loans). Servicing of real estate assets. Services for the supply of data and other servicing ancillary services. Our Mission - Create value for our clients and shareholders by offering high-standard services to maximize their profitability through innovation and operational excellence while encouraging the sustainable development of the financial system. Our Vision - Become the reference partner of our clients offering innovative products throughout the entire life cycle of loans and real estate assets management. We are looking for a Data Scientist to support the creation of new data products for the market and to collaborate with both the local Spanish team and Group/holding functions. This role offers the opportunity to grow your technical skills, contribute to strategic data projects, and act as a link between teams at different organizational levels. You are a Spanish speaker with professional English proficiency, comfortable working in an international environment. Main roles and responsabilities Act as a point of contact between the Group Data Strategy team and the local Spanish team, helping ensure clear communication and alignment. Support the local contribution to Group data initiatives, providing feedback on data availability, local needs, and business context. Help ensure that Group data standards and methodologies are correctly applied in local projects. Apply basic statistical, analytical, and machine‑learning techniques to contribute to models, indicators, and insights for new data products. Explore internal and external datasets to identify opportunities for new features and analytical improvements. Perform exploratory data analysis (EDA) to assess data quality and understand trends or patterns. Produce clear documentation, visualizations, and presentations to communicate the logic, methodology, and value of proposed data product features. Contribute to the continuous improvement of our data science methodologies and product innovation pipeline. 2–3 years of professional experience, ideally within structured environments such as consulting firms or large organizations. Bachelor degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field. Proven track record in Data projects, with hands‑on involvement in analytics, modeling, and data‑driven solutions. Proficient in SQL, Python, and Power BI for data manipulation, analysis, and visualization. Strong knowledge of Microsoft ecosystem, with experience in Azure and Databricks environments highly preferred. Familiarity with data governance principles and scalable data architectures. Fuent in English and Spanish. Personal & Organizational Skills: Highly reliable, organized, and detail‑oriented, capable of managing tasks with a project management mindset. Ability to maintain structured workflows and documentation even in technical roles. Strong soft skills: team player, positive attitude. At AS1, we are redefining how data shapes decision‑making in football — from player performance to transfer strategy. Behind every smart scouting decision, every undervalued player identified, and every strategic move in the market, there is a powerful combination of data, models, and football understanding. That is exactly what this role is about. We are looking for a Senior Data Scientist who wants to operate at the intersection of football performance, market intelligence, and advanced analytics — and who is motivated by building models that directly influence real-world decisions. Why this role exists Modern football is no longer driven by intuition alone. Clubs, agents, and decision-makers increasingly rely on: Advanced performance metrics Market intelligence and valuation systems However, the real competitive edge comes from connecting these domains into a single decision-making framework. At AS1, we are building that layer. To do so, we need a data scientist who can transform complex data into clear, actionable, and strategic insights — in environments where decisions matter and timing is critical. What you will work on This role is about owning the intelligence layer of football decision-making. You will design and deploy models that: Evaluate player performance and potential Identify market opportunities and inefficiencies Support scouting and recruitment strategies Inform player representation and transfer decisions You will work with complex, multi-source datasets including: Event and tracking data Market and transfer data Internal proprietary datasets Your work will directly impact: Player scouting and recruitment Squad building and fit analysis Transfer strategy and valuation Strategic advisory to stakeholders Much of what you will build will define how decisions are made going forward. Where you will work You will be part of a distributed team, working remotely across Europe, with a strong preference for Spain. This setup allows: Close collaboration with technical and football profiles Flexibility in execution Direct exposure to real decision-making processes How you will work You will collaborate across a multidisciplinary environment combining: Data science and machine learning expertise Football domain knowledge Business and market understanding You will work closely with: Data engineers and data providers Football analysts and scouts This role suits someone who enjoys: Building models that go beyond academic exercises Working close to decision-makers Translating complexity into clarity Balancing rigor with real-world applicability What kind of profile fits Beyond technical skills, we are looking for someone who: Think(s) in terms of impact, not just models . Is comfortable navigating ambiguity and open problems. Combines analytical depth with football intuition. Is proactive, autonomous, and solution-oriented. Enjoys working in fast-paced, high-stakes environments. Experience in football analytics is highly valued, but mindset and problem-solving ability are critical. Why this is a unique opportunity Shape how data influences player careers and transfer strategy Work at the intersection of performance analytics and football economics Build proprietary models with real-world impact Operate in a high-leverage environment with direct decision influence Contribute to the next generation of football intelligence systems We are not just analyzing the game. We are helping define how decisions in football will be made. Key responsibilities Design and implement predictive models for player performance and valuation Analyze large-scale, multi-source datasets to generate actionable insights Develop proprietary algorithms to assess player potential and team fit Collaborate with data engineers to ensure data quality and scalability Translate complex outputs into clear recommendations for non-technical stakeholders Stay at the forefront of data science and football analytics innovation Required profile 5+ years of experience in data science and machine learning Strong proficiency in Python (pandas, scikit-learn, numpy) and SQL Solid experience in predictive modeling and statistical analysis Fluent in English (Spanish is a plus) Nice to have Experience with cloud platforms (e.g. AWS) Background in football analytics Familiarity with providers such as Opta, Wyscout, or StatsBomb Experience working with event and tracking data Application process Interested candidates should send: (details missing) To: Applications will be reviewed on a rolling basis. Early applications are encouraged. Deseable #J-18808-Ljbffr
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