Lead Data Scientist

Data Science is at the core of Nielsen’s business. Our team of researchers come from diverse disciplines and they drive innovation, new product ideation, experimental design and testing, complex analysis and delivery of data insights around the world. We support all International Media clients and are located where our clients are.
Lead Data Scientist
ABOUT THIS JOB Media Data Science as a Service designs scalable and reusable tools for Nielsen Data Science and builds custom methodologies that integrate Nielsen’s state-of-the-art data assets into cutting-edge audience measurement products. The Lead Data Scientist is responsible for leading and supporting methodology, production of analytical tools and services, custom analysis, and software design. 
ABOUT YOU You’re a visionary who can also execute--you see the possibilities, then create a plan and make it happen. You understand media measurement or are able to quickly pick up domain knowledge on the job. You write production-quality code and enjoy operationalizing your solutions at scale. You’re able to shift gears quickly and adapt to changing circumstances. You also have the communication chops to translate it all into conversation or presentations, connecting strategic objectives to daily work. Seeing the big picture takes attention to detail. Keeping up with the fast-changing world of digital media measurement takes someone who recognizes that. You know what’s happening in the data science world and you’re ready to influence what’s next. 
JOB RESPONSIBILITIES • Leading and supporting analyses for Media Data Science as a Service, including custom products, syndicated products, client inquiries, and impact of changing methodologies.• Build scalable machine-learning and statistical software. • Leading prototyping and pilot programs for R&D purposes, such as integration of disparate datasets, automation, trend analyses, identifying gaps for improvements in coverage, representation/ sampling, bias reduction, indirect estimation, outlier detection, generalization, and harmonization. • Developing, documenting, implementing, and testing new audience measurement methodologies in collaboration with cross-functional teams. • Designing data production flows for automation using cloud and workflow management tools.• Collaboratively creating and managing projects, from timeline creation to project completion.• Communicating with internal stakeholders and clients. • Representing Nielsen within research and industry associations. • Managing multiple projects simultaneously • Creates, maintains, and supports data pipelines • Assisting junior members in Data Science coding best practices 
REQUIREMENTS Essential: ● Masters or PhD degree in Statistics, Social Science, Operation Research, or other hard sciences (e.g. Engineering, Computer Science, Biology, Physics etc.) with outstanding analytical expertise or equivalent experience. ● 4+ years of relevant experience. ● Experience in trend analyses, multivariate statistics (parametric/ non-parametric), sampling, bias reduction, indirect estimation, data aggregation techniques, automation, machine learning. ● Proficient in Python, Spark, and/or Scala to develop sharable software with the appropriate technical documentation ● Experience with relational and distributed database systems with expertise in tools such as Spark, Presto, and other SQL-based querying engines ● Ability to manipulate, analyze, and interpret large data sets. ● Experience with cloud based system, preferably AWS (S3, EMR, EC2, EKS)● Experience with Git or other version control tools ● Strong communication/writing skills. 
Preferred: ● Experience in Nielsen methodologies, data collection, platforms, research processes and operations. ● Domain expertise in at least one area: statistics, machine learning, sampling, audience measurement, data integration and/or digital market research. ● Experience with data visualization tools (e.g. Tableau, Spotfire, Microstrategy).● Experience with ETL frameworks like Airflow ● Experience in implementing and managing software in cloud-based environments 
WHAT WE OFFER ● A collegial team of smart, intellectually curious data scientists ● Personal and professional development opportunities ● Exciting projects and clients ● Flexibility in working hours and location ● An open, respectful collaborative environment with colleagues around the globe● Peer-driven workshops ● Conference opportunities