About The Company:
Our client is a rapidly growing post-Series B startup. Their mission is to accelerate the development of AI applications. Their first product is a suite of APIs that allow AI teams to generate high-quality ground truth data. Their customers include Alphabet (Google), Zoox, Lyft, Pinterest, Airbnb, nuTonomy, and many more, and they've become an industry standard for the self-driving car market.
They are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. They've currently completed millions of tasks a month, and will grow to complete billions of tasks monthly.
APIs include: Sensor Fusion, Semantic Segmentation, 2D Boxes/Polygons, Video, 3D Cuboids, Lines & Splines
About the role:
As our client’s first data scientist, you will lead the charge on building our analytical infrastructure and driving insights that lead to step-function improvements in how we operate. We handle millions of tasks for businesses looking to scale their ML development, and we’re looking for a talented data scientist to help us understand it all in the service of building better products. In this role, you will apply statistical models, design and interpret experiments, build mission-critical dashboards, and help structure and order our data in the pursuit of transparency over how we operate and how we can improve.
- Work closely with product, marketing, business, and ML teams to identify and answer important questions
- Set up, maintain, and scale our data analytics infrastructure
- Build critical dashboards that will guide day-to-day operations, planning, and strategic decision-making
- Iterate on your work and analyses to generate ever-better questions to answer
- Apply statistical models to identify root causes and predict the future performance of tasks, users, and products
- Design, run, and analyze experiments
- Build machine-learning models that power core operations, such as quality assessment and fraud detection
Ideally you’d have:
- 3+ years of industry experience in data science broadly
- Expert knowledge of a scientific computing language (*e.g. *R, Python) and SQL
- Strong knowledge of statistics (clustering, regression, etc.) and experimental design
- Comfort setting up and using BI tools
- Experience with ETL tools and building / maintaining a data warehouse
Nice to haves:
- A PhD or MS in a quantitative field
- Annual Salary: $200,000 + equity (depending on experience)
For additional information, please contact email@example.com