Data Scientist

Location: Bengaluru

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 Title:

Data Scientist

Location:

Bangalore

Reporting to:
Manager
- Analytics/ Senior Manager-Analytics

1. PURPOSE OF

THE ROLE

The Data Scientist will play a key role in designing and delivering data-driven solutions that enable better decision-making across the organization. This role requires strong hands-on coding skills in Python, experience with core data science libraries, and the ability to statistically validate features and models. The analyst will collaborate across teams, work efficiently with existing codebases, and apply version control and development best practices to build scalable, production-ready analytics solutions.

With intermediate SQL expertise and a solid grasp of model development workflows, the role ensures robust, interpretable, and actionable outcomes from complex data.

2. KEY TASKS AND

ACCOUNTABILITIES

Develop and maintain data science models  using Python, applying intermediate to advanced knowledge of syntax, data structures, and key libraries such as pandas and Numpy.
Perform feature engineering and statistical validation  of features and models to ensure robustness, accuracy, and business relevance.
Write clean, modular, and well-documented code  following best development practices; optionally adopt Test-Driven Development (TDD) to enable faster iteration and feedback cycles.
Collaborate with cross-functional teams  to understand data requirements, align on analytical solutions, and translate business problems into data science problems.
Read, understand, and extend existing code bases , adapting quickly to different coding styles and project structures.
Leverage version control tools like Git  for collaborative development, code management, and maintaining reproducibility of models.
Write and optimize intermediate-level SQL queries  to extract, transform, and analyze data from structured databases.
Contribute to the deployment readiness of models , ensuring outputs are interpretable, reusable, and aligned with production or decision-support use cases.
Document processes, assumptions, and outputs  clearly for stakeholder transparency, reproducibility, and future reference.
Stay up to date  with industry trends, new tools, and emerging best practices in data science, analytics, and development methodologies.

3. Qualifications, Experience, Skills

Level of educational attainment required (1 or more of the following)
Bachelor’s or master’s degree in computer science, Information Systems, Artificial Intelligence, Machine Learning, or a related field (B. Tech / BE / Masters in CS/IS/AI/ML).

Previous work experience required
Minimum of 3 years of hands-on experience in a data science or analytics role, with a proven track record of building and deploying data-driven solutions in real-world scenarios.

Technical skills required

Must Have
Python Programming (Intermediate to Advanced):
Strong grasp of syntax, data structures, and experience with libraries like pandas and Numpy.
Data Science Fundamentals:
Ability to statistically validate features and models, ensuring sound analytical rigor.
SQL (Intermediate):
Proficiency in writing queries to extract, manipulate, and analyze data from relational databases.
Version Control (GIT):
Familiarity with collaborative development using Git for code versioning and management.
Code Adaptability:
Comfortable working with and modifying existing codebases written by others.

Good To Have
Object-Oriented Programming (OOPs) in Python:  Understanding and applying OOP concepts where appropriate.
Test-Driven Development (TDD):
Awareness of TDD practices for faster iteration and improved code quality.
Model Deployment Lifecycle Knowledge:  Familiarity with reproducibility, tracking, and maintaining deployed models (though not explicitly required, it’s a plus if known).

We dream big to create future with more cheers!