Data Scientist, Dynamic Pricing & Machine Learning at Lyft

The Briefed; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Mental health benefits

Family building benefits

Parental leave 18 weeks

401(k) with match

Paid time off

Commuter benefits

Lyft credits

Job summary

Lyft is seeking a Data Scientist for Dynamic Pricing & Offer Selection to help build end-to-end pricing models using real-time and historical data. You will collaborate with Product and Engineering on a cross-functional team and influence roadmaps to improve rider and driver experiences.

Responsibilities include formalizing pricing problems, running experiments, and delivering production-ready solutions with strong communication to leadership.

Qualifications

• PhD/MS in a quantitative field with data science focus.
• 1–4+ years for PhDs or 3–5+ years for Master’s in a Data Science role.
• Proficiency with Python and SQL in a data-driven environment.

Responsibilities

• Formalize problems mathematically within the business context.
• Perform complex data analysis to identify root causes.
• Develop and fit statistical, machine learning, or optimization models.
• Write production code and ship models to production.
• Design and run simulated and live experiments.
• Analyze data and inform launch decisions.
• Communicate findings to Product, Engineering, and executives.

Skills

Python

SQL

Data analysis

Communication

Collaboration

Education

MS/PhD in Computer Science, Economics, Statistics, Mathematics

Tools

R

Matlab

Job description

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.

The Marketplace team at Lyft is responsible for accelerating the growth of the business while simultaneously delivering on key business and financial metrics, and Dynamic Pricing & Offer Selection is an integral part of that. Our team is the dynamic pricing team responsible for leveraging both real-time and historical data to set prices for every single ride at Lyft while balancing prices and ETAs to better serve our riders’ needs.

We are looking for fast learning, data-driven individuals who are passionate about tackling these open-ended problems in pricing theory and making a large, positive impact in the business. In this role, you will work closely with Product and Engineering on a cross-functional team to prototype and build end-to-end dynamic pricing models that can operate at scale. In addition, you will be expected to leverage your domain knowledge and influence existing and future roadmaps to help Lyft continue to deliver a better experience for riders and drivers.

Responsibilities:

• Partner with other scientists, colleagues in the pricing team, and with external teams to formalize problems mathematically and within the business context
• Perform complex data analysis to gain a deeper understanding of problems by identifying their root causes
• Develop and fit statistical, machine learning, or optimization models
• Write production code; collaborate with Software Engineers to ship models to production
• Design and implement both simulated and live experiments
• Analyze experimental and observational data; facilitate launch decisions
• Communicate findings to a broad audience consisting of Product, Engineering, and executive leadership

Experience:

• Data Scientist with experience in Machine Learning, Statistics, Economics, or other quantitative fields
• M.S. or Ph.D. in Computer Science, Economics, Statistics, Mathematics, or other quantitative fields
• 1-4+ years of professional experience for PhDs or 3-5+ years for Master’s in a Data Science 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
• Proficiency in SQL - able to write structured and efficient queries involving multiple 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
• Experience in causal inference, LTV modeling, econometrics, or user choice modeling preferred

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership