Applied Scientist, Machine Learning MS/PhD (2023 Start)

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on Applied Scientists within our Data Science, Machine Learning organization to help us develop and improve the models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers.

As a machine learning applied scientist you will have the opportunity to work on our machine learning investments in one of our product surfaces. You will leverage our robust data and infrastructure to develop complex models that impact millions of users across our three audiences and tackle our most challenging business problems. You will work with an engineering lead and product manager to define and solve problems which move the business metrics and ultimately help us grow our business. Once our offices reopen, we expect this role to be hybrid with some time in-office and some time remote.

Example Projects

• Forecast the supply of available dashers as well as incoming delivery demand
• Iterate and improve our recommendation, personalization and ranking algorithms which have applications in several product areas like search, autocomplete and email/push communications
• Build models for next generation pricing and pay algorithms
• Improve models used in real time vehicle routing in major metropolitan areas, to help our dashers arrive at desired locations with little to no lag/latency
• Predict preparation time for over 50,000 merchant partners
• You can find out more on our ML blog post here

• Excited and passionate — 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
• 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
• Looking for impact — ready to take on a lot of responsibility and work collaboratively with your team

• Recently finished / about to finish a PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
• Have a good understanding of many quantitative disciplines such as statistics, machine learning, operations research, causal inference, and deep understanding in at least one
• Have demonstrated familiarity with programming languages e.g. python and machine learning libraries e.g. SciKit Learn, Spark MLLib
• Have understanding of experimentation techniques e.g. A/B testing

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.

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.