Position: Data Scientist, Decisions
Company: Lyft
Category: Data Science
Experience required: 3y
English level: upper

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data Science is at the heart of Lyft’s products and decision-making. As a member of the 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.

As a Data Scientist, Decisions, you will leverage data and rigorous, analytical thinking to shape the company’s product and business decisions. You will identify and scope opportunities, shape priorities, recommend solutions, design experiments, and measure impact. You will bring a quantitative mindset to decision-making in partnership with product, business, and operations stakeholders throughout the organization. 

**Sample problems that we solve:**

What’s the marginal effect of 1min of ETA to conversion and cancels ?
Where are our drivers and passengers ?
How can we get them from point A to point B ?
What defines good pick-up and drop-off spots ?
What do trips tell us about map defects ?

**Responsibilities:**
- Leverage data and analytic frameworks to identify opportunities for growth and efficiency;
- Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action;
- Design and analyze experiments; communicate results and act on launch decisions;
- Develop analytical frameworks to monitor business and product performance;
- Establish metrics that measure the health of our products, as well as rider and driver experience;

**Experience:**
- Degree in a quantitative field such as statistics, economics, applied math, operations research, engineering or relevant work experience. Advanced degrees are preferred;
- 3+ years of industry experience in a data science or analytics role;
- Proficiency in SQL - able to write structured and efficient queries on large data sets;
- Experience in programming, especially with data science and visualization libraries in Python or R;
- Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners;