Sr. Data Scientist

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 : Senior Data Scientist

Location : Bangalore

Reporting to : Senior Manager

1. Purpose of the role

This role sits at the intersection of data science and revenue growth strategy, focused on developing advanced analytical solutions to optimize pricing, trade promotions, and product mix. The candidate will lead the end-to-end design, deployment, and automation of machine learning models and statistical frameworks that support commercial decision-making, predictive scenario planning, and real-time performance tracking.

By leveraging internal and external data sources—including transactional, market, and customer-level data—this role will deliver insights into price elasticity, promotional lift, channel efficiency, and category dynamics. The goal is to drive measurable improvements in gross margin, ROI on trade spend, and volume growth through data-informed strategies.

2. Key tasks & accountabilities

• Design and implement price elasticity models using linear regression, log-log models, and hierarchical Bayesian frameworks to understand consumer response to pricing changes across channels and segments.
• Build uplift models (e.g., Linear Regression, XGBoost for treatment effect) to evaluate promotional effectiveness and isolate true incremental sales vs. base volume.
• Develop demand forecasting models using ARIMA, SARIMAX, and Prophet, integrating external factors such as seasonality, promotions, and competitor activity, time-series clustering and k-means segmentation to group SKUs, customers, and geographies for targeted pricing and promotion strategies.
• Construct assortment optimization models using conjoint analysis, choice modeling, and market basket analysis to support category planning and shelf optimization.
• Use Monte Carlo simulations and what-if scenario modeling to assess revenue impact under varying pricing, promo, and mix conditions.
• Conduct hypothesis testing (t-tests, ANOVA, chi-square) to evaluate statistical significance of pricing and promotional changes.
• Create LTV (lifetime value) and customer churn models to prioritize trade investment decisions and drive customer retention strategies.
• Integrate Nielsen, IRI, and internal POS data to build unified datasets for modeling and advanced analytics in SQL, Python (pandas, statsmodels, scikit-learn), and Azure Databricks environments.
• Automate reporting processes and real-time dashboards for price pack architecture (PPA), promotion performance tracking, and margin simulation using advanced Excel and Python.
• Lead post-event analytics using pre / post experimental designs, including difference-in-differences (DiD) methods to evaluate business interventions.
• Collaborate with Revenue Management, Finance, and Sales leaders to convert insights into pricing corridors, discount policies, and promotional guardrails.
• Translate complex statistical outputs into clear, executive-ready insights with actionable recommendations for business impact.
• Continuously refine model performance through feature engineering, model validation, and hyperparameter tuning to ensure accuracy and scalability.
• Provide mentorship to junior analysts, enhancing their skills in modeling, statistics, and commercial storytelling.
• Maintain documentation of model assumptions, business rules, and statistical parameters to ensure transparency and reproducibility.

Other Competencies Required

Business Environment

Main Characteristics :

3. Qualifications, Experience, Skills

Level of educational attainment required :

Previous work experience required

Technical skills required

And above all of this, an undying love for beer!

We dream big to create future with more cheers .