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
Role: Senior Data Scientist
Location: Hyderabad / Chennai
Years of Experience: 6+ years
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.
Mission
Roche has established the Global Analytics and Technology Center of Excellence (GATE) to drive analytics- and technology-driven solutions by partnering with Roche affiliates across the globe. GATE enables data-led decision-making and innovation across healthcare and biotech operations
You will work closely with the U.S. Strategic Customer Support Consulting team dedicated to Roche's most important diagnostic customers — large reference laboratories, hospital networks, and integrated health systems. The team's mandate is to help these customers run more resilient, efficient, and cost-effective supply chain operations.
Your Opportunity
As the Senior Data Scientist in this team, you will own the forecasting, optimization, and machine learning work that underpins our customer engagements. You will inherit and evolve an existing production forecasting engine, harden it for scale across accounts, and extend it into a broader supply chain optimization framework. You will also provide recommendations and strategic support on other various customer supply chain initiatives, related to forecasting, optimization and machine learning.
This is a hybrid technical–consultative role. Roughly half your impact will come from the depth and rigor of the models you build; the other half will come from your ability to sit across the table from a senior customer stakeholder, understand their operational reality, and convert a model output into a decision they act on.
Experience in Gen AI, LLM, NLP, and ML Ops will be considered an added advantage, supporting Roche's future-ready analytics and AI roadmap.
How You'll Work
You will be part of a wider data and analytics community at Roche, and your best work will happen in partnership with it. You will collaborate closely with our product and visualization teams to make sure the models you build reach business and customer teams as clear, usable views — translating forecasts, inventory recommendations, and risk signals into the reports and interfaces people actually work from. You must operate well with ambiguity and changing priorities.
Key Responsibilities:
- Serve as the data science lead on strategic consulting engagements for Roche's top diagnostic customers, partnering with consultants and account teams from problem framing through to delivered impact
- Engage directly with business consultants — primarily through virtual forums, to scope problems, test hypotheses, and align on success measures
- Translate customer supply chain pain points — stockouts, over-ordering, bottlenecks, working capital lock-up, erratic consumption, expiry and wastage — into well-posed modelling problems, and then into deployed, usable solutions
- Deliver consumption forecasting and replenishment recommendations at the customer account level, helping customers order the right quantity at the right time, and helping Roche plan against real downstream demand
- Work internally with other technology teams to ensure solutions built can be used throughout the transition to ASPIRE and other similar system changes (i.e. Agility/ARID migration to Snowflake, Google to Microsoft)
- Drive and support industry-leading initiatives such as a Digital Twin Risk Analysis for scenario planning and modeling, Inventory Rightsizing and Safety Stock Analysis tools, Freight and Network Optimization modeling, and Carbon Footprint tracking and reduction
- Collaborate on Agentic AI capabilities on top of existing and future databases and tools
- Build reusable models, methodologies, and accelerators that the consulting team can deploy repeatedly across accounts, rather than rebuilding bespoke solutions each time
- Present modelling results, business cases, and quantified impact (service level, working capital, wastage reduction) to senior internal and external audiences through clear, persuasive storytelling
- Capture learning from each engagement and feed it back into the team's models, methods, and scalable offerings
Who You Are:
You are a hands-on technical builder with 6+ years of experience in hands-on data science, with demonstrable specialization in forecasting. You possess strong analytical problem-solving skills and thrive in a technical–consultative role, turning complex operational processes into automated, production-ready models.
Qualifications & Technical Skillset:
- Master's or Bachelor’s in Statistics, Operations Research, Computer Science, Applied Mathematics, Econometrics, or a related quantitative discipline
- 6+ years of hands-on data science experience, with demonstrable specialization in forecasting — you have owned production forecasting systems, not just built proofs of concept
- Deep, practical command of state-of-the-art time-series techniques: hierarchical forecasting and reconciliation, intermittent-demand methods, probabilistic/quantile forecasting, global vs. local model strategies, and modern neural forecasting architectures
- Hands-on experience building models using algorithms and techniques such as multivariate regression, time series analysis, XGBoost, clustering, classification, OLS regression, and causal inference methods
- Proven experience in inventory optimization, replenishment policy design, and/or supply chain network modelling, with a track record of delivering measurable service-level or working-capital impact
- Demonstrated experience working directly with external customers or clients — you are comfortable running workshops, presenting to senior stakeholders, handling challenges in the room, and building credibility with non-technical audiences. Prior consulting, client-facing data science, or customer success experience is strongly preferred
- Exceptional communication and storytelling skills — you can move fluently between a model diagnostic conversation with an engineer and a value conversation with a customer executive
- Comfortable building trust and running effective customer engagements remotely — virtual workshops, video-based executive presentations, and asynchronous collaboration across time zones
- Good working knowledge of reporting and visualization practice — you understand how dashboards are designed and consumed, and can partner effectively with visualization teams to specify what business and customer audiences need to see. Familiarity with tools such as Power BI, Tableau, or Qlik is an advantage
- Strong programming skills in Python and SQL, with experience using libraries and frameworks such as scikit-learn, statsmodels, PyTorch/TensorFlow, pandas, NumPy, Spark, and forecasting-specific tooling (e.g., Prophet, statsforecast/Nixtla, GluonTS, Darts)
- Experience with optimization solvers and OR libraries (e.g., Gurobi, CPLEX, OR-Tools, PuLP, Pyomo)
- Experience deploying and maintaining models in cloud environments (AWS/GCP/Azure) with modern ML Ops tooling (MLflow, Airflow/Dagster, Kedro, Docker, CI/CD)
- Experience taking models from prototype to productized capability
- Strong analytical and problem-solving skills with a data-driven mindset
Strong to have:
- Understanding of diagnostics and pharmaceutical supply chains — reagents and consumables, cold chain, shelf life and expiry management, installed-base-driven consumption, and lab workflow dynamics
- Experience designing alerting and exception-scoring models in a production decision-support setting
- Familiarity with GxP, validated environments, and regulated-industry documentation practices
- Experience with GenAI, LLMs, NLP, and agentic workflows applied to operational decision support
- Prior experience working in a global capability centre or shared-services model, partnering across time zones and affiliates
- Experience presenting to internal and external business stakeholders (?)
*Note: This job description is intended as a general guideline for the responsibilities and qualifications required for this position. It is not an exhaustive list, and responsibilities may evolve and change based on business needs
Who we are
A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.
Let’s build a healthier future, together.
Roche is an Equal Opportunity Employer.
