AI / ML Engineer II

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 and crediting.
• Design comprehensive ML workflows, develop reliable data pipelines (using PySpark/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.

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