AI / ML Data Scientist II

Thenielsencompany; Bengaluru; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

Nielsen in Bengaluru seeks an AI/ML Data Scientist II to design, build, and deploy scalable ML systems, with robust software engineering practices and data science methods.

You will work on audience measurement data, develop end-to-end ML workflows using Databricks and AWS S3, and present clear data-driven recommendations to stakeholders.

Qualifications

• Bachelor's degree or higher in Mathematics, Statistics, CS, Data Science or related field.
• 3-6 years of professional Data Engineer or similar quantitative experience.
• Ability to tell a story from data with clear analyses.
• Proficiency in Python, PySpark, SQL, AI/ML.
• Strong statistics knowledge including hypothesis testing and experimental design.
• Experience with Tableau for data visualization.
• MDL concepts familiarity is a plus.

Responsibilities

• Implement, test, and optimize econometric, statistical, and ML models to improve accuracy.
• Identify AI opportunities in projects and implement them.
• Learn Audience Measurement and the associated digital meter tech.
• Design ML workflows, build data pipelines (Databricks/AWS S3), train/evaluate models, summarize results.
• Integrate, clean, and transform data from diverse sources for ML inputs.
• Develop, share, and maintain production-grade code with engineering best practices.
• Incorporate quality checks throughout ML lifecycle to catch errors early.
• Create visualizations (Tableau) to support analysis and communicate insights.
• Translate research into data-driven recommendations addressing business needs.

Skills

Python

PySpark

SQL

AI/ML

Statistics

Tableau

MDL familiarity

Education

Bachelor's degree or higher in a quantitative field

Tools

Databricks

AWS S3

Job description

About the Role

This job description outlines the responsibilities and qualifications for an AI / ML Data Scientist II role with a primary focus on designing, building, and deploying scalable machine learning systems, software engineering best practices, and the application of AI/ML principles within Machine Learning and Data Science contexts.

Audience is everything! Nielsen offers the world's most complete measurement of media-viewing behavior. Our data scientists and ML engineers leverage the best data assets and modeling methods to build consistent and comparable metrics of the media landscape in multiple countries. We help the world's biggest brands make better and faster media and marketing decisions.

Responsibilities

• Implement, test, and optimize econometric, statistical, and Machine Learning (ML) models to enhance data accuracy and reporting.
• Identified the AI opportunities in existing and new projects and implemented them.
• Quickly learn and become an expert in Audience Measurement and the associated digital meter technology for data collection.
• Design comprehensive ML workflows, develop reliable data pipelines (using Databricks/AWS S3), execute sophisticated model training and evaluation, and clearly summarize results.
• Identify, integrate, clean, and transform data from disparate and complex data sources to ensure high-quality inputs for ML models.
• Develop, share, and maintain efficient, well-documented, production-quality code following software engineering best practices.
• Proactively incorporate quality checks throughout the ML development lifecycle to detect and correct errors swiftly.
• Create simple, meaningful visualizations (e.g., using Tableau) to effectively support data analysis and clearly communicate insights and findings to stakeholders.
• Translate complex research findings into clear, data-driven recommendations that address business needs and drive product/technology improvements.
• Partner closely with department stakeholders (Engineering, Data Science, Product, Technology) to manage timelines, share data, execute tests, and present results.

Key Skills & Qualifications

• Bachelor's Degree or higher in Mathematics, Statistics, Computer Science, Data Science, Data Engineering, or a closely related quantitative field.
• 3-6 years of professional experience in a Data Engineer or similar quantitative role.
• Proven ability to manipulate, analyze, and interpret complex data sources to effectively "tell a story from data" through impactful analyses.
• Proficiency in Python, PySpark, SQL, Artificial intelligence and Machine learning
• Deep understanding and application of Statistics, including hypothesis testing, regression analysis, and experimental design.
• Experience with trending and visualizing data using tools like Tableau
• Familiarity with Media Data Lake (MDL) concepts is a plus.

Business Skills

• Excellent oral and written communication
• Self-motivation and an ability to handle multiple competing priorities in a fast-paced environment
• Strong interpersonal skills and the ability to develop effective relationships with other team members, including remotely.