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Roche

Global pharmaceuticals and diagnostics company

Data Science Engagement Lead

Data ScienceConfirmed live in the last 24 hours
Full-timeSan José Province, San José, Costa RicaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's or master's degree in Data Science, Statistics, Economics, Artificial Intelligence and Machine Learning, Computer Science, Business Analytics, or another quantitative field.
  • At least 10 years of experience in Data Science or Analytics, including at least 3 years leading data science teams and mentoring data scientists, with a track record of measurable business impact through predictive modelling and causal inference or experimentation; commercial or marketing analytics experience is ideal.
  • Strong hands-on predictive modelling expertise, including classification on skewed data with imbalance handling such as SMOTE and class weighting; ensemble and tree-based models including LightGBM, XGBoost and CatBoost; linear models; anomaly detection; unsupervised methods such as clustering and segmentation; and time-series forecasting such as ARIMA and Prophet.
  • Experience with rigorous model validation and explainability, including SHAP, precision-recall and calibration methods for imbalanced problems.
  • Deep expertise in causal inference and experimentation, including experimental design, A/B testing, quasi-experimental methods and econometrics.
  • Hands-on experience building Marketing Mix Models and multi-touch attribution models, including regression-based, time-decay, Markov-chain and Shapley-value methods, using frameworks such as Google Meridian, PyMC-Marketing, Meta Robyn, LightweightMMM, Orbit, PyMC or Stan. This includes model diagnostics such as convergence, priors and posterior predictive checks, and translating outputs into budget optimization, response curves and scenario simulations.
  • Expert proficiency in Python and SQL, with strong experience in Spark for distributed computing, Airflow, Git, AWS, and Tableau or an equivalent visualization and storytelling tool.
  • Exposure to and recent experience with generative AI tools and large language models such as OpenAI, Claude, Gemini and DeepSeek, and coding assistants such as GitHub Copilot, plus experience building AI agents with frameworks such as LangChain, LangGraph, AutoGen or CrewAI.

Responsibilities

  • Lead the Predictive AI & Optimization and Causal AI & Experimentation data science sub-streams supporting commercial teams, owning their technical direction and delivery.
  • Work directly with product owners to translate business questions into predictive, causal and optimization solutions, and grow a team of about seven data scientists.
  • Lead, mentor and develop Senior Data Scientists and Data Scientists across both sub-streams, building technical depth, modular coding standards and agile delivery habits.
  • Lead the design, calibration and validation of Bayesian and frequentist Marketing Mix Models that account for adstock, saturation, seasonality and hierarchical or geo-level effects.
  • Oversee multi-touch attribution and brand performance analytics, and translate results into practical recommendations on channel mix and spend.
  • Design and govern experiments, including A/B tests, quasi-experimental designs such as difference-in-differences and synthetic control, and econometric analysis, to measure the impact of commercial initiatives.
  • Oversee the design and delivery of predictive models for commercial use cases, including classification on highly imbalanced data, anomaly detection, segmentation and time-series forecasting.
  • Use optimization to turn predictions into decisions, including budget and resource allocation, response curves, ROI and mROI analysis, and scenario-planning simulations.
  • Rapidly design and build proofs of concept, prototypes and business case studies, including generative AI and agent-based solutions where they add value, to demonstrate tangible impact.
  • Set methodological standards for each sub-stream, decide which approaches suit each problem and explain why alternatives are unsuitable.
  • Review model designs, validation results and critical code, and resolve technical blockers.
  • Present findings and trade-offs clearly to technical and non-technical audiences so complex model results support informed decisions.
  • Work with global cross-functional teams in an agile environment, including demos, reviews and retrospectives to improve deliverables.
  • Ensure reproducibility, documentation and peer review across all delivered models.

Desired Qualifications

  • Recognized professional certifications in Data Science, Machine Learning, Cloud AI Platforms or Advanced Analytics are an advantage.
  • Commercial or marketing analytics experience is ideal.

About the Company

Roche

Global pharmaceuticals and diagnostics company

Roche is a global leader in pharmaceuticals and diagnostics. It develops medicines and diagnostic tools that help detect, monitor, and treat diseases, using research and biotechnology to drive new therapies and tests. Roche combines drug development with in-house diagnostic products to support personalized medicine, where treatments are tailored to individual patients based on test results. Its approach differs from many peers by integrating drug discovery with diagnostic capabilities and by expanding its research through strategic acquisitions (like Genentech) to strengthen its biotechnology and R&D capabilities. The company’s goal is to improve patient outcomes and healthcare worldwide by delivering reliable medicines, accurate diagnostic tests, and data-driven care.

Company size
1-10
Company stage
IPO
Headquarters
Basel, Switzerland
Founded
1896

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