Research Scientist, Decision Science Products

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The Decision Science Products team (DSP) is a cross-functional group of engineers and scientists focused on leveraging science, product, and engineering to drive better business decisions for Lyft. Rather than focusing on a specific slice of the business, DSP looks horizontally across Lyft to drive change in the areas of greatest opportunity, with the end goal of improving how we operate our business day to day.

DSP sits at the intersection of Lyft’s product, growth, operations, and finance teams, and serves as a strategic partner for our senior leadership team. The team tackles challenges across many technical disciplines – including time series forecasting, causal inference, optimization, and machine learning. Here is a short list of problems we’re working on:

  • Manage overall business health and performance measurement
  • Develop and publish operational forecasts for our key business metrics
  • Build ROI and risk management tools to guide budget investments
  • Understand and optimize between key growth and efficiency levers across Lyft
  • Advise on strategic investments and long-term business trajectory

We are hiring motivated experts who can push the boundaries of our technical work. The ideal candidate is a critical thinker, is passionate about solving mathematical problems with data, and is excited about working in a fast-paced, innovative and collegial environment.

Responsibilities:


  • Partner with team members on product, operations, science, and finance to translate business problems into technical solutions

  • Develop and operationalize measurement frameworks and scenario planning tools to drive decision-making across all of our markets

  • Publish and improve forecasts performance for our key business metrics

  • Construct and fit statistical, machine learning, or optimization models to define relationships between levers across different parts of our business


Experience & Skills:

  • M.S. or Ph.D. in Economics, Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields

  • 4+ years professional experience

  • Passion for solving unstructured and non-standard mathematical problems

  • Experience solving operational challenges such as supply chain, demand chain, and/or financial planning problems

  • End-to-end experience with data, including querying, aggregation, analysis, and visualization

  • Proficiency with Python, or another interpreted programming language like R or Matlab

  • Willingness to collaborate and communicate with others to solve a problem


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