About the Team
Come help us build the world’s most reliable on-demand, logistics engine for delivery! We’re bringing on talented data scientists to help us develop and improve the models that power DoorDash’s three-sided marketplace of consumers, merchants, and dashers.
About the Role
As a support-focused Machine Learning Scientist you will have the opportunity to identify and prioritize machine learning investments across our support ecosystem. You will leverage our robust data and infrastructure to develop natural language processing and causal inference models that impact millions of users across our three audiences. You will partner with an engineering lead and product manager to set the strategy that moves the business metrics which help us grow our business.
You’re excited about this opportunity because you will…
- Lead the development of DoorDash’s support chatbot: Applying active learning, semi-supervised learning, weak label generation, and data augmentation strategies to improve the consumer, dasher, and merchant support experience
- Drive the personalization of DoorDash’s credit and refunds policies: Using uplift/heterogeneous treatment effect models and contextual bandits to improve consumer retention after negative delivery experiences
- Spearhead the creation of next generation agent tools: Building contextual bandits to recommend replies to support agents and generative models for agent text auto-completion to improve the consumer, dasher, and merchant experience while reducing agent effort
- 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
- You can find out more on our ML blog post here
We’re excited about you because…
- 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
- Desire for impact — ready to take on a lot of responsibility and work collaboratively with your team
- 4+ years of industry experience developing optimization models with business impact — more experience preferred
- 1+ years of industry experience serving in a tech lead role
- M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
- Deep understanding of natural language processing techniques and procedures for efficiently acquiring and validating human-labeled data
- Good understanding of many quantitative disciplines such as statistics, machine learning, operations research, and causal inference
- Demonstrated familiarity with programming languages e.g. python and machine learning libraries e.g. SciKit Learn, Spark MLLib
- Experience productionizing and A/B testing different machine learning models
- Familiarity with advanced causal inferences techniques and contextual bandit algorithms preferred
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.
Pursuant to the Colorado Fair Pay Act, the base salary range in Colorado for this position is $141,525.00 –$191,475.00 , plus opportunities for equity and commission. Compensation in other geographies may vary.
If you need any accommodations, please inform your recruiting contact upon initial connection.
Jobs available in location : San Francisco, CA; United States – Remote