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Global brand, mid-level generalist ML role, and Bangalore metro location increase candidate competition.
Core ML and data engineering skills are transferable, but media-measurement domain knowledge creates moderate bias.
Explicit 3–6 years requirement plus mandatory ML, Databricks/AWS, Python, PySpark, and SQL skills create strict filters.
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Design, build, and deploy scalable machine learning systems with a focus on econometric, statistical, and ML models to enhance data accuracy and reporting.
Develop reliable data pipelines (Databricks/AWS S3), conduct model training and evaluation, and maintain production-quality code following software engineering best practices.
Translate complex research into actionable data-driven recommendations and communicate insights through visualizations (e.g., Tableau) to stakeholders.
Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, Data Engineering, or related quantitative field.
3-6 years of professional experience in Data Engineering or similar quantitative roles.
Proficiency in Python, PySpark, SQL, and Machine Learning including AI principles.
Experience with statistical methods including hypothesis testing, regression analysis, and experimental design.
Experienced in working with complex and disparate data sources to extract actionable insights, particularly in media measurement contexts.
Skilled in coordinating cross-functional teams including Engineering, Data Science, Product, and Technology to deliver projects and communicate results.
Ability to quickly learn domain-specific technologies such as Audience Measurement and operate efficiently in fast-paced, multi-priority environments.