Machine Learning Researcher

At Nielsen, we believe that career growth is a partnership. You ultimately own, fuel and set the journey. By joining our team of nearly 14,000 associates, you will become part of a community that will help you to succeed. We champion you because when you succeed, we do too. Embark on a new initiative, explore a fresh approach, and take license to think big, so we can all continuously improve. We enable your best to power our future.

The Big Data and Panel Integration team within the Data Science organization focuses

on improving and enhancing Nielsen’s highly successful audience measurement

products out in the marketplace for advertising and content measurement. As part of

this exciting team, this position will focus on developing new methodologies to

measure audiences across platforms (including on “connected” or “over the top”

devices, smart tv’s, or set top boxes) and on evaluating and integrating new data

assets and partners into Nielsen’s existing methodologies in order to enhance or

expand the data delivered to clients.

The Senior Data Scientist role provides an opportunity to contribute to methodological

innovation in the exciting and fast changing world of media measurement. This position

will develop new methodologies to measure audiences across platforms and integrate

new big data data assets into Nielsen’s existing methodologies. This is an ideal

position to grow as a researcher, contribute to innovative products, and deploy cutting

edge methodologies across platforms in audience measurement methodology.

In this role, you will work closely with other members of the team to optimize the

current codebase, create simulation environments and pipelines, and have the

opportunity to conduct research that will enhance the utility of our data. You will also

write new coding packages to support the refinement processes of behavioral media

tuning data (e.g. meter crediting rules, big data editing rules, big data refinement

models) by producing production ready code (scalable, reusable/modular). In addition,

you will have the opportunity to grow your data science skills (coding, statistics)

through all aspects of the data science workflow and data product lifecycle.

Responsibilities would range from methodology development, analysis, lightweight

automation to designing and building robust/scalable code packages.

**Responsibilities**:

- Own reproducible data science projects end-to-end.
- Deploy and maintain data pipelines and models in a production environment.
- Work with cross-functional teams to productionize, validate, and optimize methodologies.
- Conduct research and analytics to ensure methodologies are fit for purpose and working as intended; troubleshoot, diagnose, and resolve when they are not.
- Provide technical mentorship.
- Communicate research findings to varying audiences.
- Develop, implement and maintain good programming standards and practices across our data science and analytics codebases.
- Champion and govern best practices for data use and software development.
- Use git and cloud development tools extensively to iterate and improve data science workstreams.

**Skills**:

- Bachelor’s or Master’s (preferred) degree in a quantitative research field, such as computer science, data science, statistics, mathematics, biological/physical sciences, etc.
- 3-5 years code development/research experience in a business setting.
- Strong proficiency with Java, Python, Spark, SQL, Unix, git, and AWS (S3 and EC2).
- Excellent verbal and written communication skills.
- Excellent software engineering fundamentals.
- Excellent debugging skills.
- Excellent machine learning fundamentals.
- Outstanding statistical and analytical skills.
- Collaborative code development experience, including version control, unit/integration testing, code review and sharing.
- Curiosity and skepticism.