At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Job Summary The Strategic Research team within the Nielsen One Data Science organization focuses on expanding and enhancing Nielsen’s digital measurement and optimization products. This branch of the team supports Digital Content Ratings as well as Nielsen Streaming Signals. The latter is a new and innovative product launching for streaming providers to optimize their ad inventory in real time. The Lead Data Scientist role provides an opportunity to innovate and implement cutting edge technologies in the exciting and dynamic world of content measurement and digital advertising. This position is ideal for a seasoned data scientist to apply their experience and skills to building sustainable processes and robust data products. It is also an opportunity to gain valuable leadership and mentoring experience while overseeing data science development projects. In this role, you will work closely with other members of the team, often as the technical lead, to optimize the current codebase, create simulation environments and pipelines, and conduct research that will enhance the utility of our data. You will have the opportunity to grow your technical knowledge while using your experience with data science methodologies to improve our product offerings. Responsibilities include the following: ML research and implementation, investigative data analysis, code optimization, ETL and automation, creating robust/scalable packages for production pipelines, project management, technical oversight (e.g. leading code reviews and managing documentation), and mentoring.
Responsibilities
Research and implement methods for demographic prediction for measurement and optimization use cases.
Optimize use of available data assets by developing frameworks for evaluation.
Translate new methodologies into functional modules, including unit tests and quality control checks.
Provide data-driven recommendations for promoting enhancements to production, including client-focused simulations.
Identify root causes and solve any bugs or quality escapes.
Ensure detailed documentation of new methodologies, research findings, and best practices.
Work with cross-functional internal stakeholders to develop solutions for key business problems.
Create and manage projects from beginning to end including design, execution and summarization Mentor and provide technical oversight to junior associates, e.g. by leading code reviews and establishing best practices.
Explain complex data science concepts in simple terms to non-technical audiences, including clients.
Key Skills
Bachelor’s degree in a quantitative programming field, such as computer science, data science, engineering, statistics, mathematics, biological/physical sciences, etc.
5+ years of professional work experience in Statistics, Data Science, and/or related disciplines.
Python mastery.
Experience with sophisticated data mining & modeling solutions and the tools that support them (e.g. Scikit-learn, PyTorch, PyMC3).
Experience with relational and distributed database systems with expertise in tools such as Spark, Presto, and other SQL-based querying engines.
Experience with task orchestration frameworks like Airflow.
Experience with DevOps tools and CI/CD workflows including Git.
Well organized, self-motivated and an ability to handle multiple competing priorities in a fast-paced environment.
