Senior Data Scientist, Optimization - Supply Demand Balancing - DoorDashView Company Profile
- Job Title
- Senior Data Scientist, Optimization - Supply Demand Balancing
- Job Location
- San Francisco, CA; New York, NY; Seattle, WA; United States - Remote
- Job Description
About the Team
Come help us build the world's most reliable on-demand, logistics engine for delivery! We are bringing on talented senior Data Scientists to help us develop and improve the supply lever models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. Dasher pay and incentives is a fundamental area of investment for DoorDash to enable high-quality deliveries with maximum efficiency. The Supply-Demand DSML team has among the coolest problems to solve at scale, optimizing budget spend over multiple channels for delivering dasher incentives. We are looking for Operations Research Scientists, Economists, Mathematicians, Statisticians and other quantitative disciplines to drive system-wide changes and create major business impact. You can read more about the types of Data Scientists we are looking for in our blog post Wanted: Data Scientists with Technical Brilliance AND Business Sense.
About the Role
As a Data Scientist and domain expert, you will help identify opportunities in Logistics and lead the development of core production-grade optimization and machine learning models at scale. You will work with other data scientists, engineers, and product managers to develop and iterate on models to help us grow our business by making order fulfillment more efficient
You’re excited about this opportunity because you will…
- Lead the development and improvement of DoorDash's proactive and reactive supply levers at the intersection of OR, ML, RL, and economics.
- Drive first-generation model development in areas of insurance and dasher safety
- Build production-grade algorithms and models that improve the experience of millions of Merchants, Consumers and Dashers across the world.
- Leverage our simulation platform to run large scale simulations to generate insights and accelerate model iteration speed.
- Find innovative ways to drive business impact by combining new data signals from our marketplace with efficient optimization algorithms to improve decision-making throughout DoorDash Logistics systems.
- Apply stratification, variance reduction, and other advanced experiment design techniques to create A/B tests to efficiently measure the impact of your innovations while minimizing risk to the broader system
- Mentor and uplevel a talented team of Data Scientists, and ML Engineers
- You can find out more on our ML blog post here
We’re excited about you because…
- Desire for impact — you’re excited about delivering impact independently and collaboratively with your team for the business
- High-energy and confident — you keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down
- You’re an owner — driven, focused, and quick to take ownership of your work
- Humble — you’re willing to jump in and you’re open to feedback
- Adaptable, resilient, and able to thrive in ambiguity — things change quickly in our fast-paced startup and you’ll need to be able to keep up!
- Growth-minded — you’re eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
- 3+ years of industry experience of developing optimization and machine learning models with business impact — more experience preferred
- M.S., or PhD. in Operations Research, Computer Science, Math or other related quantitative fields
- Demonstrated expertise with Object Oriented programming and modern languages and libraries e.g. python and libraries for optimization and ML e.g. Gurobi, Google OR-Tools, SciKit Learn
- Experience of shipping production-grade optimization models
- Experience of developing and running large scale simulations for model prototyping and validation
- Deep familiarity with complex systems such as Marketplaces, and domain deep domain knowledge in OR (stochastic optimization, convex optimization, dynamic programming, MIPs, sequential decision models), applied experience with Machine Learning (DL/ NN, Tree Based models,etc.), contextual bandits and reinforcement learning problems.
- Good understanding of many quantitative disciplines such as statistics, machine learning, operations research, and causal inference
At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods.
DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.
Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.
Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.
If you need any accommodations, please inform your recruiting contact upon initial connection.
DoorDash Headquarters Location
San Francisco, CA
DoorDash Company Size
Between 8,600 - 8,600 employees
DoorDash Founded Year
DoorDash Total Amount Raised
DoorDash Funding RoundsView funding details