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Data Scientist, Causal Inference
2 weeks ago
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
Data Science is at the heart of Lyft's products and decision-making. As a member of the Rider Science team, you will work in a dynamic environment, where we embrace moving quickly to build the world's best transportation. Data Scientists take on a variety of problems, ranging from shaping critical business decisions to building algorithms that power our internal and external products. We're looking for passionate, driven Data Scientists to take on some of the most interesting and impactful problems in ridesharing.
We are looking for a Data Scientist - Algorithms with chops in Economics, Statistics, or other quantitative fields to join the Rider Segments team. In it, you will leverage data, analytical thinking, and rigorous machine learning and causal modeling to bring to life zero-to-one products tailored to our most impactful and strategic rider segments and their use cases. We're looking for execution-oriented scientists who are passionate about solving challenging problems with data and mathematical models, and are excited about working in a fast-paced, innovative environment. You will bring a quantitative mindset to decision-making in partnership with engineers, product, business, and marketing stakeholders across organizations and drive roadmaps to create products solving the needs of millions of riders.
**You will report to a Data Science Manager in the Rider team.**
**Responsibilities**:
- Partner with other scientists and colleagues in the rider segments team, and with external teams across driver, marketplace and business to frame problems mathematically and within the business context
- Perform exploratory data analysis to gain a deeper understanding of problems
- Develop and fit statistical, causal and machine learning models
- Design, implement and analyze experiments or leverage other quasi-experimental observational methodologies to measure performance
- Communicate findings and facilitate launch decisions
- Develop causal measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
**Experience**:
- M.S. or Ph.D. in Economics, Statistics, or other quantitative fields
- 1-2+ years of professional experience for PhDs or 2-4+ years for Master's in a data scientist role
- 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
- Familiar with SQL - able to write structured and efficient queries on large data sets
- Ability to collaborate and communicate with others to solve a problem
- Strong oral and written communication skills, and ability to collaborate with cross-functional partners
**Benefits**:
- Extended health and dental coverage options, along with life insurance and disability benefits
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- Access to a Lyft funded Health Care Savings Account
- RRSP plan to help save for your future
- In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
- Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
- Subsidized commuter benefits
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Toronto area is CAD $108,000 - $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
