About the Team
Come help us build the world's most reliable on-demand, logistics engine for delivery! We're looking for an experienced data scientist 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 here
We’re excited about you because you have…
- 4+ years of industry experience developing optimization models with business impact, including 1+ year(s) 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
- You must be located near one of our engineering hubs which includes: San Francisco, Sunnyvale, Los Angeles, Seattle, and New York
- Deep understanding of natural language processing techniques and procedures for efficiently acquiring and validating human-labeled data
- Good understanding of quantitative disciplines such as statistics, machine learning, operations research, and causal inference
- Familiarity with programming languages e.g. python and machine learning libraries e.g. SciKit Learn, Spark MLLib
- Experience producing and A/B testing different machine learning models Familiarity with advanced causal inferences techniques and contextual bandit algorithms preferred
About DoorDash
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.
Compensation
The location-specific base salary range for this position is listed below. Compensation in other geographies may vary.
Actual compensation within the pay range will be decided based on factors including, but not limited to, skills, prior relevant experience, and specific work location. For roles that are available to be filled remotely, base salary is localized according to employee work location. Please discuss your intended work location with your recruiter for more information.
DoorDash cares about you and your overall well-being, and that’s why we offer a comprehensive benefits package, for full-time employees, that includes healthcare benefits, a 401(k) plan including an employer match, short-term and long-term disability coverage, basic life insurance, wellbeing benefits, paid time off, paid parental leave, and several paid holidays, among others.
In addition to base salary, the compensation package for this role also includes opportunities for equity grants.
We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on August 21, 2023.
Please see the independent bias audit report covering our use of Covey here.
