About the Team
We are bringing on talented senior Data Scientists to help us develop and improve the models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. We are looking for Economists, Physicists, Mathematicians, Statisticians, and senior quantitative researchers from all disciplines. 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 Director of Machine Learning Data Science, you will have the opportunity to lead and grow a team of data scientists to identify and prioritize our machine learning investments in our cross-company Operational Excellence product vertical. Your team 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 in the areas of Fraud, Customer Support, Delivery Experience, Company Forecasting, Consumer ETAs, and more to follow. You will partner with Directors of Engineering and Product Management to set the strategy that moves the business metrics which help us grow our business.
You’re excited about this opportunity because you will…
- Build fraud detection models to predict actions by bad actors
- Employ natural language processing methodologies to respond to customer requests with high quality and low cost
- Go deep into the user journey post-checkout to understand where their experience can be improved and how we can use machine learning to do so
- Improve consumer ETAs (delivery times) accuracy to reduce early and late deliveries
- Create a cross-company forecasting platform, eventually for self-service by technical and non-technical practitioners
- You can find out more on our ML blog post here
We’re excited about you because…
- You're 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
- You're Humble — you’re willing to jump in and you’re open to feedback
- 8+ years of industry experience hiring and managing teams of data scientists / machine learning experts
- M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
- Good understanding of many quantitative disciplines such as statistics, machine learning, operations research, causal inference, and deep understanding in at least one
- Demonstrated familiarity with programming languages e.g. python and machine learning libraries e.g. SciKit Learn, Spark MLLib
Why You’ll Love Working at DoorDash
We are leaders – Leadership is not limited to our management team. It’s something everyone at DoorDash embraces and embodies.
We are operators – We believe the only way to predict the future is to build it. Creating solutions to lead our company and our industry is what we do on every project, every day.
We are learners – Everyone here is continually learning on the job, no matter if we’ve been in a role for one year or one minute. We are committed to learning and implementing what is best for our customers, merchants, and dashers.
We are one team – The magic of DoorDash is our people, together making our inspiring goals attainable and driving us to greater heights.
At DoorDash, our mission to empower local economies shapes how our team members move quickly and always learn and reiterate to support merchants, Dashers and the communities we serve. 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. Read more on the DoorDash website, the DoorDash blog, the DoorDash Engineering blog, and the DoorDash Careers page.
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. Our leaders seek the truth and welcome big, hairy, audacious questions. We are grounded in our company values, and we make intentional decisions that are both logical and display empathy for our range of users—from Dashers to Merchants to Customers.
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.
If you need any accommodations, please inform your recruiting contact upon initial connection.