AB InBev—Senior Data Scientist

Job description

Description: 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: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager - Analytics 1. PURPOSE OF ROLE As a Senior Data Scientist, you will play a pivotal role in designing and building production-ready data science solutions for AB InBev’s analytics initiatives. You will lead data science efforts, guiding the team to scale and standardize AI-driven solutions across multiple ABI markets. This role requires a mix of hands-on model development, product integration knowledge, stakeholder management, and a vision for driving AI innovation at scale. 2. KEY TASKS AND ACCOUNTABILITIES • Lead and execute end-to-end data science projects from: Data collection and preprocessing, Model development, Deployment, Performance monitoring. • Build robust, reusable Python-based pipelines and contribute to improving code quality and standardization. • Working with Senior Analytics Manager to create project plans, and design analytics roadmap. • Work closely with business stakeholders to understand business context and present complex analytical insights into actionable business strategies to non-technical stakeholders. • Mentor and coach junior data scientists in advanced techniques, code quality, and product integration principles. • Passion for building large-scale, AI-powered products, ensuring seamless integration with business workflows. • Stay updated with emerging trends in AI and data science, continuously improving methodologies and tools. 3. QUALIFICATIONS Bachelor's or master's degree in Computer Science, Information Systems, Economics, Artificial Intelligence, Data Science, Machine Learning, or a related field (B. Tech / BE / Masters in CS/IS/AI/ML). 4. WORK EXPERIENCE 5+ years of hands-on experience in a data science or analytics role with proven track record of building, deploying, and maintaining machine learning models for data-driven solutions in real-world scenarios. 5. TECHNICAL SKILLS REQUIRED(Mandatory) •Hands-on experience in Advanced programming in Python for ML pipeline development, SQL (Intermediate to Advanced) for analytical query writing and optimization and excel (intermediate to advanced) for quick data manipulation. •Experience with Git for collaborative development and version control. •Experience with any cloud platform – Azure, AWS, GCP or Databricks. •Expertise in multiple Statistics and ML techniques (e.g. classification, regression, forecasting, recommendation, optimization) •Experience with Object-Oriented Programming (OOPs) in Python to build standardized libraries and tools. 6. GOOD TO HAVE SKILLS(Optional) •Exposure to MLOps/CI-CD (Docker, pipelines). •Experience working closely with engineering/product teams using Agile delivery practices. •Experience in experiment tracking, model lineage, and reproducibility best practices. •Experience with A/B testing, causal inference frameworks, or experimentation platforms. •Experience with one of the following frameworks - PyTorch, TensorFlow, JAX. •PySpark for large-scale data processing and distributed computing. And above all of this, an undying love for beer! We dream big to create a future with more cheers.