Data Scientist, Autonomous Vehicle Infrastructure Analytics

Full time

Employment Information

One way to picture building autonomous vehicles is that autonomy is the product of a factory. That factory consists of multiple production lines: collecting and labeling datasets, training neural networks, testing the vehicle itself, and so forth. The AV Infrastructure Team within NVIDIA’s autonomous vehicles (AV) program are the factory builders. We are looking for an experienced Data Scientist to join our AV Infra Analytics Team to help understand those production lines, optimize them, and ultimately improve the performance of the factory itself so that NVIDIA can ship outstanding autonomy on an ambitious timeline.

What You’ll Be Doing:

  • Our team supports multiple areas – data ingestion, drive data quality, labeling and dataset generation, and many others. Your focus will be to own one or more of these areas, working with the associated engineering and product teams, and create metrics that represent the user experience.
  • At the same time, we also make it easier for users to answer their own questions. That requires understanding their needs deeply and how the data we have available can help. You’ll use those insights to develop ETL pipelines and shared services while working to fill instrumentation gaps to create a clearer picture.
  • To do that well, you’ll need to be comfortable up and down the analytics stack – connecting to data, cleaning it, writing your own ETL pipelines, and building dashboards in a variety of tools. Our work is very hands-on!
  • Your work will undoubtedly be viewed regularly by senior leaders and be used to make decisions about how time and engineering resources get spent as we work hard to nurture a culture of data-driven decision making. Knowledge and credibility are key to making that happen.

What We Need to See:

  • Demonstrated ability in data science, analytics, quantitative business/management consulting, or related academic research with the experience to be highly self-sufficient.
  • Deep technical proficiency with standard data analytics tools such as Python (Pandas, Jupyter Notebooks, etc.) and SQL plus the ability to write clean, maintainable code in a collaborative environment.
  • Bachelor’s degree, higher, or equivalent experience
  • 8+ years of experience in a similar or related role
  • Outstanding communication skills for distilling sophisticated topics down to understandable, impactful conclusions.

Ways to Stand Out from the crowd:

  • Experience working with time series data from continuously running processes
  • Demonstrated attention to detail and ability to spot patterns in complex data
  • Familiarity with autonomous vehicles or large scale compute infrastructure

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re creative and autonomous, we want to hear from you.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables outstanding creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence.

The base salary range is 168,000 USD - 322,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


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