GRM Data Analyst

Job Title: GRM Data Analyst

Location: Bengaluru, India

Reporting to: Senior Program Manager

Role Purpose: Join AB InBev's Global Risk Management (GRM) function in Bengaluru, India. The GRM team is responsible for identifying top business risks and implementing mitigative actions through internal audits, fostering process improvements and adding value to the business. The GRM Data Science team collaborates with global finance leaders to support risk identification by developing scalable analytics tools for data-driven risk monitoring and financial data analysis.

As a GRM Data Analyst, you will be expected to demonstrate end-to-end ownership, from hands-on development using SQL and Python (including implementing ML models for predictive analytics) to product delivery and stakeholder management.

Key Responsibilities:

• Risk Analytics Development: Design and build scalable analytics solutions and risk scoring frameworks to pinpoint risk areas, anomalies, and high-risk transactions. Utilize SQL, Python, and machine learning models for these tasks.
• Apply Scalable & Best Practices: Ensure the development of clean, modular code, standardized logic, and reusable frameworks to produce reliable, production-ready analytics.
• Enable Decisions through Insights: Translate complex analytics into clear dashboards and outputs that inform audit planning, risk monitoring, and strategic business decisions.
• Drive Adoption & Business Impact: Integrate analytics into business workflows, ensuring that outputs are well-understood, trusted, and actively used in decision-making processes.
• Be a Mentor: Provide guidance and feedback to junior analysts and interns, fostering their development within the team.

Success Metrics:

• Analytics are consistently trusted and utilized to drive business decisions.
• Demonstrable improvements in outcomes, including earlier risk detection and significant reduction in manual effort.
• Strong stakeholder trust, with the ability to bridge technical delivery with business requirements.

Qualifications:

• Bachelor's or Master's degree in Engineering, Finance, Business, or a related field.
• Minimum of 2 years of hands-on experience in analytics roles, with a proven record of solving business problems using data.
• Experience in delivering analytics for finance, risk management, or internal audit functions is advantageous.

Required Technical Skills:

• SQL: Proficiency in writing production-quality queries for large financial and transactional datasets.
• Python: Experience with data analysis using PySpark, feature engineering, ML Ops, CI/CD, and model prototyping.
• Coding Standards: Ability to write clean, modular, and maintainable code.
• Defining KPIs: Skill in translating business objectives into well-defined, actionable metrics.

Preferred Technical Skills:

• Power BI: Experience in dashboard development and creating business-facing analytics products.
• Risk Analytics: Familiarity with anomaly detection, risk scoring, predictive analytics, or smart sampling techniques.
• ML: Experience in evaluating model performance, understanding false positives, explainability, and business usefulness.
• GenAI: Exposure to generative AI use cases such as document review, summarization, retrieval, or theme extraction.

Required Functional Skills:

• Ability to transform ambiguous business problems into structured analytics outputs and metrics.
• Excellent communication skills, capable of conveying findings clearly to both technical and non-technical audiences.
• A strong end-to-end product ownership mindset.
• A willingness and aptitude to coach junior team members and interns.

Preferred Functional Skills:

• Experience in stakeholder management within complex, cross-functional environments.
• Proven ability in prioritization and delivery within fast-paced settings.
• Knowledge of risk management, internal audit, or finance/supply chain processes.

Why This Role is Unique: This position offers a blend of deep technical expertise and business acumen, moving beyond pure research or reporting. The role demands the creation of analytics that become integral to risk and audit decision-making, requiring technical depth, business judgment, and the discipline to ensure analytics are scalable and usable.

And above all, a passion for creating a future with more cheers!