Senior Data Scientist, Algorithms - Primetime Pricing

Socotra, Inc.; San Francisco (CA); Hybrid; USD 148,000 - 185,000; Full time

Job summary

A leading tech company is seeking a Data Scientist to join their Marketplace team in San Francisco. You will engage in dynamic pricing models, utilize statistical analysis, and collaborate with cross-functional teams to improve pricing strategies. The role requires strong analytical skills and a passion for tackling open-ended problems in pricing theory. As part of a diverse and inclusive workplace, you will have the opportunity to influence product roadmaps while being supported by comprehensive benefits and a hybrid work environment.

Benefits

Great medical, dental, and vision insurance

Mental health benefits

Family building benefits

Child care and pet benefits

401(k) plan

Discretionary paid time off

18 weeks of paid parental leave

Subsidized commuter benefits

Exclusive employee discounts and perks

Qualifications

• 1-4+ years of experience for PhDs or 3-5+ years for Master's in Data Science.
• End-to-end experience with data, including querying, aggregation, analysis, and visualization.
• Experience in causal inference or LTV modeling preferred.

Responsibilities

• Develop and fit statistical, machine learning, or optimization models.
• Perform complex data analysis to understand problems.
• Communicate findings to Product, Engineering, and executive leadership.

Skills

Machine Learning

Statistics

Data Analysis

Collaboration

Communication

Education

M.S. or Ph.D. in Computer Science

M.S. or Ph.D. in Statistics

M.S. or Ph.D. in Mathematics

M.S. or Ph.D. in Economics

Tools

Python

SQL

Job description

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

The Marketplace team at Lyft is responsible for accelerating the growth of the business while simultaneously delivering on key business and financial metrics, and Prime Time & 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 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
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected range of pay for this position in the San Francisco area is $148,000 - $185,000. 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.