Data Scientist

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates , resources, and opportunities to unleash their full potential. The power we create together — when we combine your strengths with ours — is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Data Scientist Location: Bangalore (Onsite) Reporting to: Senior Manager PURPOSE OF ROLE Contributing to the Data Science efforts of AB InBev s Global Test Learn Platform — an analytics engine and SDK that powers experiment design and uplift measurement across multiple markets. The platform integrates with a web UI product and enables business teams to design, execute, and measure the impact of interventions using rigorous statistical and ML methods. The role requires an AI-first mindset, strong analytical rigor, and the ability to convert business questions into actionable data-driven recommendations. KEY TASKS AND ACCOUNTABILITIES Partner with business, product, and analytics stakeholders to define analytical approaches and deliver models and insights that drive measurable outcomes. Develop predictive, descriptive, and prescriptive models — including hypothesis testing, forecasting, optimization, and statistical inference. Perform data exploration, feature engineering, and model evaluation using structured and unstructured data at scale (Databricks, PySpark ). Contribute production-quality Python code to the platform’s SDK and support its integration with the web UI product. Build and maintain reproducible, scalable ML pipelines — from feature engineering through model serving and monitoring. Power platform capabilities with LLMs — automated insight generation, AI-enabled UI features, and intelligent summarization of analytical outputs. Communicate findings, assumptions, and recommendations clearly to both technical and non-technical audiences. Support experimentation design, A/B testing, and causal impact measurement where relevant. Contribute to documentation, best practices, data governance, and continuous improvement of data science standards. QUALIFICATIONS, EXPERIENCE, SKILLS Education: B.Tech / B.E. / Masters in Statistics, Mathematics, Computer Science, Economics / Econometrics, or a related quantitative field. Experience: Minimum 3 years of relevant experience in data science or analytics. Preferred industry exposure: FMCG, CPG, supply chain, commercial analytics, finance, marketing, or operations analytics. Experience working with large datasets and cloud or distributed data environments. Experience deploying analytics solutions for internal or external clients. Technical/Functional Skills: Mandatory Skills: Python – Expert (End-to-end ML pipelines, OOP, packaging, and testing) Statistics – Advanced (Probability, inference, hypothesis testing, regression, experimental design) Machine Learning – Advanced (Regression, classification, clustering, forecasting, optimization) Data SQL – Advanced (Pandas, NumPy, SciPy, SQL) PySpark Databricks – Intermediate (Large-scale distributed data processing) GenAI / LLMs – Intermediate (RAG pipelines, prompt engineering, LLM-powered feature development for product use cases) Git – Intermediate (Branching, PRs, code reviews) Cloud (Azure) – Intermediate (Cloud-based analytics environments) Communication Stakeholder Management – Advanced (Storytelling with data, cross-functional collaboration) Preferred (Good to have) Skills: MLflow, Docker, Streamlit, Power BI – Intermediate MLOps / Production analytics environments – Intermediate Experimentation design causal inference (A/B testing, DiD , Synthetic Control, PSM) – Intermediate statsmodels , scikit-learn, econometric toolkits – Intermediate LLM-powered applications (custom RAGs, vector databases, LLM chains) – Intermediate And above all of this, an undying love for beer! We dream big to create a future with more cheers.