Lead Data Scientist

Responsibilities

• Research, design, develop, implement and test econometric, statistical, optimization and machine learning models.
• Design, write and test modules for Nielsen analytics platforms using Python, R, SQL and/or Spark.
• Utilize advanced computational/statistics libraries including Spark MLlib, Scikit-learn, SciPy, StatsModels or R.
• Collaborate with cross functional Data Science, Product, and Technology teams to integrate best practices from across the organization
• Provide leadership and guidance for the team in the of adoption of new tools and technologies to improve our core capabilities
• Execute and refine the roadmap to upgrade the modeling/forecasting/control functions of the team to improve upon the core service KPI’s
• Gain a deep understanding of the Audio methodology supported by the team
• Ensure product quality, stability, and scalability by facilitating code reviews and driving best
• practices like modular code, unit tests, and incorporating CI/CD workflows
• Explain complex data science (e.g. model-related) concepts in simple terms to non-technical internal and external audiences

• 5+ years of professional work experience in Statistics, Data Science, and/or related disciplines, with focus on delivering analytics software solutions in a production environment
• Expertise with relational and distributed database systems with expertise in tools such as Spark, Presto, and other SQL-based querying engines
• Expertise in coding and testing of analytical modules using Python, SQL and Spark.
• Expertise in at least one statistical software or machine learning package, such as R or Scikit-learn
• Expertise with optimization techniques and tools such as AIMMS, Gurobi, etc
• Expertise with DevOps tools and CI/CD workflows including Git
• Expertise with sophisticated data mining forecasting & modeling solutions and the tools that support them such as Scikit-learn, PyTorch, and PyMC3
• Well-organized, clear communication, and an ability to handle multiple competing priorities in a fast-paced environment
• Graduate/Post Graduate degree in Statistics, Economics, Applied Mathematics, Computer Science, Engineering or other Quantitative field of study
• Exceptional problem solving skills. Abilities to solve problems independently and within a cross-functional team to resolve any hurdles in the projects
• Critical thinking skills to evaluate results in order to make timely decisions
• Mentor and provide guidance to other data scientists
• (Preferable) Experience working in cloud-based environments such as Azure, AWS, or GCP
• (Preferable) Experience with ETL frameworks like Airflow
• (Preferable) Domain expertise in survey sampling and/or audience measurement