Senior Data Scientist, Machine Learning - Delivery Excellence

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 improve the delivery service quality for DoorDash's three-sided marketplace of consumers, merchants, and dashers. As a fundamental area of investment for DoorDash, Delivery Excellence has among the coolest problems to solve at scale and creates a major impact on the company and our customers. We are looking for Machine Learning Scientists, Economists, 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.

As a senior Data Scientist, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop inference and ML models that impact millions of users across our three audiences and tackle our most challenging business problems. You will work with other data scientists, engineers, analysts, and product managers to develop and iterate on models to help us grow our business and provide the best service quality for our customers.

• Build statistical and ML models that run in production to help enhance the consumer experience by reducing cancellations, pickup waiting times, delivery lateness, missing and incorrect items and non fulfilled orders
• Own the modeling life cycle end-to-end including feature creation, model development and prototyping, experimentation, monitoring and explainability, and model maintenance 
• Being exposed to new opportunities where delivery quality can be used as a lever for demand shaping, search ranking, customer segmentation, etc
• Mentor and uplevel a talented team of Data Scientists and ML Engineers
• You can find out more on our ML blog post here

• 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

Experience

• 3+ years industry experience of developing advanced statistical and machine learning models with business impact — more experience preferred
• M.S., or PhD. in Machine Learning, Statistics, Computer Science, Applied Mathematics or other related quantitative fields
• Demonstrated expertise with programming languages, e.g. python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, TensorFlow, etc
• Deep understanding of complex systems such as Marketplaces, and domain knowledge in two or more of the following: Machine Learning, Causal Inference, Operations Research, Forecasting and Experimentation
• Experience of shipping production-grade ML models and optimization systems, and designing sophisticated experimentation techniques

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.

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.