At Lyft, community is what we are and it’s what we do. It’s what makes us different. To create the best ride for all, we start in our own community by creating an open, inclusive, and diverse organization where all team members are recognized for what they bring.
As a Research Scientist on Experimentation, you will collaborate with a team of fellow scientists, engineers and designers to advance information-based decision making at Lyft. Your role is to develop and apply novel methodologies to improve the design, analysis, and interpretation of the hundreds of experiments we run each week on our company-wide experimentation platform. The ideal candidate is passionate about experimentation, applied statistics, and data-informed decision making, while bringing substantial hands-on experience from past projects involving A/B testing or causal inference.
Our team owns an experimentation platform used across Lyft to run hundreds of experiments every week. You will be responsible for using statistics, programming and an understanding of user needs to improve our experimentation best practices and develop new methodologies to accelerate our rate of learning. The ideal candidate is a critical thinker who is passionate about continually improving how we use information from experiments to make smarter decisions for our users.
- Work with Engineers, Product Managers, and Partner Teams to frame experimentation problems, both mathematically and within the business context
- Perform exploratory data analysis and literature reviews to gain a deeper understanding of emerging experimentation best practices
- Explore and evaluate statistical, inferential and machine learning models
- Write production modeling code; collaborate with Software Engineers to implement algorithms in production
- Consult as an expert to other teams running live traffic experiments
Experience & Skills:
- M.S. or Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields
- 4+ years professional experience
- Direct experience with online experimentation or causal inference
- Passion for solving unstructured and non-standard mathematical 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
Lyft is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Lyft does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Lyft will also consider for employment qualified applicants with arrest and conviction records.
To apply for this job please visit boards.greenhouse.io.
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