Applied Scientist- Pricing, Dynamic Pricing & Offer Selection

Responsibilities

• Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context.
• Write production quality code.
• Design, build and deploy production-grade ML and Optimization models.
• Able to build custom methods and tooling beyond off-the-shelf libraries.
• Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems.
• Evaluate machine learning systems against business goals.
• Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems.
• Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes.
• Drive collaboration and coordination with cross-functional teams.

Requirements

• Experience M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields.
• 2+ years of algorithms experience in a technology company setting.
• Proficiency with Python and working in a production coding environment.
• Passion for solving unstructured and non-standard mathematical problems and building impactful machine learning models leveraging expertise in one or multiple fields.
• Strong understanding of machine learning methodologies, with proven experience with building and evaluating optimization or machine learning models.
• Strong verbal and written communication skills with a good track record of collaborating with others to solve a problem.

Qualifications

• Experience with developing and deploying machine learning models in production environments.
• Experience with optimization techniques and algorithms.
• Experience with data analysis and statistical modeling.
• Experience with cloud-based platforms such as AWS, Google Cloud, or Azure.

Skills

• Machine Learning
• Operations Research
• Python
• Optimization
• Data Analysis

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.
• 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.

Pay

Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Schedule

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