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Data Scientist

New York, NY
Full-Time
Salary Range : $150,000

As a Data Scientist you will be solving our hardest data science problems and challenges:

  • Predicting business behavior from dozens of data sources and validating them against ground truth
  • Exploring new data sets and extracting the signal that powers our products
  • Helping to build the data science culture and infrastructure to rapidly move from hypothesis to impact

The Role:

Data Science is at the heart of who we are. You will design and execute experiments to extract signals from hundreds of data sources, design and develop tooling to make the team more effective, and closely collaborate with product managers and engineers.  

We are looking for someone who:

  • Finds innovative solutions to problems in statistics, experiment design and distributed machine learning (we use Python libraries and Spark extensively)
  • Sets high personal standards for research design that increase iteration speed and ensure reproducibility of results
  • Approaches data as an artefact of the real-world and develop repeatable strategies for validating results against ground truth
  • Develops techniques to detect and explore anomalies in our data, uncover the source and address in a way that improves our product
  • Thrives in high-performing, collaborative teams with short, high-impact research cycles

What makes this job interesting?

  • Technical challenge: We are solving some of the hardest problems in the world related to entity resolution and pushing to make new discoveries. You will be critical to our success.
  • Impact: Data science at many companies focuses on making better product development and business decisions. Data science is the core of our actual product! 
  • Learning: We’re tackling problems with exciting data that don’t have obvious solutions.  Every day brings new opportunities to learn about data science and our world.

Our ideal candidate will:

  • Bring 3-4+ years of industry experience in statistics, experiment design, distributed machine learning and data engineering
  • Effectively communicate with technical and non-technical audiences
  • Have an advanced degree in a quantitative discipline (e.g. Computer Science, Mathematics, Physics, etc.)

Bonus points if you:

  • Have experience combining diverse sets of data at scale

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