# Engagement Lead - Data Science at Roche

Roche is hiring an Engagement Lead - Data Science in Hyderabad, India. Level rates it Builds AI ●●●●; you can [apply on Roche](https://jobsbylevel.com/go/ecc3cbb3-7a92-4af4-b674-469b85249069?utm_medium=ai-agent).

AI Level 4, AI centrality 85 out of 100. Hyderabad.

## Details

- Company: [Roche](https://jobsbylevel.com/companies/roche)
- AI level: AI Level 4 (score 85 out of 100)
- Location: Hyderabad
- Posted: November 12, 2026
- Apply: https://jobsbylevel.com/go/ecc3cbb3-7a92-4af4-b674-469b85249069?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=engagement-lead-data-science-at-roche-eee83d

## Prepare for this job

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## Description

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters. The Position Engagement Lead - Data Scientist Roche India – Roche Services & Solutions Hyderabad A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. Roche has established the Global Analytics and Technology Center of Excellence (GATE) as part of Roche Services & Solutions (RSS) India to drive analytics and technology-driven solutions by partnering with Roche affiliates across the globe. RSS is a global division operating in an agile organizational setup without extensive hierarchical structure, where all our employees lead from every seat, and inspirational leadership, and an entrepreneurial customer-centric mindset are our core values. Your Opportunity As Engagement Lead , you will lead two data science sub-streams supporting commercial teams: Predictive AI & Optimization and Causal AI & Experimentation . You will own the technical direction and delivery of both. You will work directly with product owners to turn business questions into predictive, causal and optimization solutions, and you will grow a team of about 7 data scientists. This is a hands-on leadership role. You will review models and code, unblock the team quickly, and be accountable for the quality and business impact of everything the two sub-streams deliver. Key Responsibilities: Lead, mentor and develop Senior Data Scientists and Data Scientists across both sub-streams. Build technical depth, modular coding standards and agile delivery habits Lead the design, calibration and validation of Bayesian and frequentist Marketing Mix Models (MMM). Models should account for adstock, saturation, seasonality and hierarchical or geo-level effects Oversee multi-touch attribution (MTA) and brand performance analytics. Translate the results into practical recommendations on channel mix and spend Design and govern experiments, including A/B tests, quasi-experimental designs (e.g., difference-in-differences, synthetic control) and econometric analysis, to measure the true impact of commercial initiatives Oversee the design and delivery of predictive models for commercial use cases. This includes classification on highly imbalanced data, anomaly detection, segmentation and time-series forecasting Turn predictions into decisions through optimization: budget and resource allocation, response curves, ROI/mROI analysis and scenario-planning simulations Rapid Prototyping & Business Value: Quickly design and build proofs of concept, prototypes and business case studies, including GenAI- and agent-based solutions where they add value , to show tangible impact Set the methodological standards for each sub-stream. Decide which approaches are suitable for a given problem, and explain why others are not Stay close to the work: review model designs, validation results and critical code, and resolve technical blockers quickly Present findings and trade-offs clearly to both technical and non-technical audiences, so that complex model results lead to confident decisions Work with global cross-functional teams in an agile environment, including demos, reviews and retrospectives to keep improving deliverables Ensure reproducibility, documentation and peer review across all models delivered Who You Are You are an accomplished data science leader with deep expertise in both predictive modelling and causal inference. You

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