Data Scientist, Algorithms - Pricing - Rider Engagement

Description

The company builds transportation products, and data science drives its product and business decisions. The Pricing team sets prices for all rideshare products and supports new initiatives. Within it, Rider Engagement owns the algorithms and systems for incentive offers, budget management, operational control and real-time optimization, which are among the marketplace's most impactful levers for short and long term results.

You will work on a cross-functional team with Product, Engineering and Analytics to design and refine incentive levers, and to prototype and build end-to-end solutions that run at scale. You will tackle open-ended problems in pricing theory and use your domain knowledge to shape current and future roadmaps, improving the experience for riders and drivers.

The company wants people who learn quickly, work from data, and enjoy open-ended problems with a large business impact.

Responsibilities

• Frame problems mathematically and in business context with scientists, engineers, product managers and business partners.
• Write production code and work with software engineers to put algorithms into live systems and keep those systems robust.
• Build and fit statistical, machine learning or optimization models, and deploy production-grade models for business problems.
• Design, run and analyse experiments that guide decisions and priorities.
• Define metrics and measurement methods to track product health and the effects on user and marketplace outcomes.
• Carry out in-depth analysis to understand problems better and find new product and business opportunities.
• Coordinate with cross-functional teams and present findings to Product, Engineering and executive leadership.

Requirements

• Master's or PhD in machine learning, operations research, statistics, computer science or another quantitative field.
• PhD holders need 1 to 4+ years of professional data science experience at a technology company. Master's holders need 3 to 5+ years in the same setting.
• Demonstrated experience building and evaluating optimization or machine learning models.
• Proficiency in Python and experience working in a production coding environment.
• A genuine interest in solving unstructured, non-standard mathematical problems.
• Hands-on experience across the data lifecycle: querying, aggregation, analysis and visualization.
• Strong verbal and written communication, and the ability to work with others to solve problems.

Conditions

Hybrid role based in the office three days a week, on Mondays, Wednesdays and Thursdays. The company considers this in-office attendance an essential function of the role. Your recruiter can explain the in-office perks. Hybrid roles may also work from anywhere for up to 4 weeks per year.

Expected base pay in the San Francisco area is $128,000-160,000 per year. Pay depends on qualifications, experience and location, and excludes any equity, bonus or benefits. Your recruiter can confirm the range for your location during hiring.

The company welcomes applicants of all backgrounds and considers all qualified candidates.

Benefits

• Medical, dental and vision insurance options, with more programs available once enrolled.
• Mental health benefits and family building benefits.
• Child care and pet benefits.
• 401(k) plan.
• 12 observed holidays. Salaried team members get discretionary paid time off, and hourly team members get 15 days of paid time off.
• 18 weeks of paid parental leave for biological, adoptive and foster parents.
• Subsidized commuter benefits.
• Access to the company Pink, an exclusive chance for team members to test new Ridership Program benefits.