Senior Data Scientist Marketing Mix Modeling

Job title

Senior Data Scientist Marketing Mix Modeling

Location

Hyderabad

Opella is the self-care challenger with the purest and third-largest portfolio in the Over-The-Counter (OTC) & Vitamins, Minerals & Supplements (VMS) market globally.

Our mission is to bring health in people’s hands by making self-care as simple as it should be. For half a billion consumers worldwide – and counting.

At the core of this mission is our 100 loved brands, our 11,000-strong global team, our 13 best-in-class manufacturing sites and 4 specialized science and innovation development centers. Headquartered in France, Opella is the proud maker of many of the world’s most loved brands, including Allegra, Buscopan, Doliprane, Dulcolax, Enterogermina, Essentiale and Mucosolvan.

As a globally certified B Corp company, we are active players in the journey towards healthier people and planet. Find out more about our mission at www.opella.com.

About the job

The Advertising & Promotion (A&P) Analytics team builds the data science and decision-support systems that guide how Opella invests its global marketing budget across brands, channels, and markets. We combine Marketing Mix Modeling, scenario analysis, and mathematical optimization to turn measurement into action — helping marketing, finance, and brand stakeholders evaluate trade-offs and commit to multi-million-euro investment decisions. Our work spans the full lifecycle: from response modeling, through scenario and what-if engines, to production APIs and stakeholder-facing tools.

Who You Are

You are a senior data scientist who thrives at the intersection of modeling, optimization, and product thinking, comfortable owning complex problems end-to-end — from framing the business question, to choosing the right modeling approach, to shipping a robust system that stakeholders actually use. You partner closely with engineers, product, and business stakeholders, moving comfortably between deep technical work and stakeholder conversations — translating modeling choices into business trade-offs, and business questions into well-scoped problems. You enjoy challenging the status quo to make sure Opella's AI solutions are scientifically sound, operationally reliable, and impactful for the patients and consumers of tomorrow.

Own problems end-to-end

from framing and modeling, through experimentation and productionization, to monitoring and adoption.

Design and build decision systems combining response modeling (MMM, attribution, uplift), scenario analysis, and optimization — including budget allocation and what-if tools that let stakeholders evaluate trade-offs across channels, brands, markets, and constraints.

Productionize scenario-optimization engines and APIs with a focus on robustness, performance, and interpretability.

Apply expertise in machine learning, statistics, time-series forecasting, optimization, and Generative AI, and use data analysis, visualization, and storytelling to scope, define, and deliver AI-based data products.

Contribute to the team's technical direction through code review, design discussions, and knowledge sharing, partnering closely with product, engineering, MLOps, and business stakeholders.

Invest in long-term code health: refactor where foundations need strengthening, pay down technical debt, and prefer maintainable, well-tested solutions over short-term workarounds.

Main responsibilities

Hands-on AI/ML modeling experience with complex datasets, with strong theoretical grounding in most of: supervised/unsupervised learning, Bayesian statistics, mathematical optimization (LP/MILP, heuristics), simulation and what-if analysis.

Demonstrated experience designing and shipping decision-support systems end-to-end (not just notebooks) — production code, APIs, monitoring, and stakeholder adoption — in agile, product-focused environments.

Experience with Marketing Mix Modeling, marketing/commercial analytics, recommender systems, or similar response/decisioning problems is a strong plus.

Comfortable in cloud and high-performance computing environments (AWS preferred; also Databricks, Azure).

Excellent written and verbal communication, business analysis, and data storytelling — able to translate technical work for marketing and finance audiences — and a demonstrated ability to collaborate effectively in cross-functional teams (data scientists, engineers, MLOps, product, business).

Previous experience in business areas such as Marketing, Finance, Manufacturing & Supply, or Operations.

Nice to have

experience in life sciences, healthcare, or CPG, and in a complex global organization.

About you

Education

PhD in a quantitative discipline (mathematics, computer science, operations research, engineering, physics, statistics, economics, or similar) with strong coding skills, OR Master's in a relevant domain with 4+ years of analytical / applied data science experience.

Optimization & Operations Research

Practical experience formulating and solving optimization problems with solvers and modeling frameworks such as Gurobi, CPLEX, Pyomo, OR-Tools, or similar — balancing solution quality, runtime, robustness, and interpretability in stakeholder-facing systems.

Econometric Modelling

Practical experience designing and executing econometric models (special focus on linear models). General knowledge of causal analysis using non-experimental data. Experience with Bayesian Linear Regression and MCMC sampling is desirable. Experience with IVs, Diff-in-Diffs, Regression Discontinuity approaches is welcome.

Programming & Software Engineering

Expertise in Python (Scala, Kotlin, or Java a plus), with strong OOP, design patterns, modular architecture, coding standards, version control, testing, and software engineering best practices.

Strong commitment to maintainable, sustainable code: comfortable refactoring legacy components, raising the engineering bar through reviews, and choosing solutions that age well over