Applied Scientist- Pricing, Dynamic Pricing & Offer Selection

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 141,000 - 176,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan with company match

Paid time off

Job summary

United States Digital Space LLC is seeking an Applied Scientist specializing in Machine Learning and Operations Research to develop mathematical models and productionalize scalable pipelines powering pricing and ETA decisions in our two-sided marketplace.

The role emphasizes collaboration with Pricing, Product, Engineers and Analysts in a fast-paced environment, translating complex business problems into reliable decision frameworks at scale.

Qualifications

• 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.
• Strong ability to translate complex problems into mathematical formulations.
• Excellent communication and collaboration across teams.

Responsibilities

• Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically.
• Write production quality code and deploy ML and Optimization models.
• Build proof-of-concept analyses and scalable ML/Optimization solutions.
• Evaluate ML systems against business goals and ensure robustness in live systems.
• Establish metrics to monitor product health and impact on outcomes.
• Collaborate across Pricing, Product, Engineers, and Analysts.

Skills

Machine Learning

Operations Research

Python

Optimization

Data analysis

Education

M.S. or Ph.D. in ML, OR, Statistics, CS

Tools

ML pipelines

Optimization libraries

Job description

At the company, 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 Pricing team is a centerpiece of the company’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention.

As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts.

We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks.

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

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

**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 the company credits and complimentary the company Pink membership

the company is an equal opportunity employer committed to an inclusive workplace that fosters belonging. 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, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

the company highly values having employees working in-office to foster a collaborative work environment and company culture. 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. the company considers working in the office at least 3 days per week to be an essential function of this hybrid role. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $140,800 - $176,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location.