Data science drives everything we do here at Nielsen. Our statistical research is at the forefront of an industry moving at the speed of light. In this role on the Digital Product team, your work on innovative methodologies and data optimization will directly impact our business and our clients.
- Work alongside scientists and engineers as the subject matter expert for building machine learning pipelines in our cloud environment.
- Collaborate with product and research teams to design and validate data and learning algorithms.
- Identify and implement features that improve algorithm efficiency and scalability.
- Create software components that can be shared and reused across Nielsen teams and processes.
- Develop, implement and maintain good programming standards and practices across our analytics codebase.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing for usability, re-designing for greater scalability.
A LITTLE BIT ABOUT YOU
You're a visionary who can also execute--you see the possibilities, then create a plan and make it happen. You're experienced building, debugging, and optimizing machine learning pipelines, and you're not afraid to take a risk or two. You also have the communication chops to translate it all into conversation or presentations, connecting strategic objectives to daily work. Your influence extends in all directions, plus you're a great mentor to junior team members. While you've worked with global cross-functional teams, you can also put your head down and focus on independent projects. 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 big data and you're ready to influence what's next.
- Graduate degree in Computer Science, Engineering, Statistics, Mathematics, Operations Research, or other relevant scientific field.
- 3+ years of experience in a Data Engineer or Data Scientist role
- Experience performing root cause analysis on internal and external data and analytics systems.
- Working knowledge of distributed databases.
- Strong project management and organizational skills.
- Advanced working knowledge of SQL, Python, and Spark
- Experience with data pipeline and workflow management tools: Airflow, Luigi, etc.
- Experience with the Hadoop ecosystem
- Experience using source control: Git / Bitbucket
- Experience with cloud services: Azure, AWS, Google
- Exposure to statistical languages: SAS, R, Julia
- Experience with object-oriented/object-functional languages: Python, Scala, Java, C++, etc.