Data Science Tech Lead, Machine Learning

Key Skills

Machine learning techniques, Mathematical modeling, Python Programming, PyTorch, Scikit-learn, SQL, Statistical modeling, TensorFlow

Job Description

About the Team

Come help us build the world's most reliable on-demand, logistics engine for delivery!

We are looking for a Tech Lead for our Growth Machine Learning team. The team is responsible for building the ML that powers our growth platform, responsible for intelligence of our systems ranging from smart user notifications, efficient marketing prospects, and new user recommendations for DoorDash's three-sided marketplace of consumers, merchants, and dashers.

About the Role

You will be part of a team of world-class engineers in Machine Learning science, redefining the new user acquisition and discovery experience through cutting edge approaches, and defining effective approaches to realize DoorDash’s pricing strategy. You will be a tech lead on the team that ensures we provide a consistent, personalized experience to our users, no matter where they sit on their journey with us, and help make critical optimization algorithms that drive effective promotions and targeting across our various customer bases. You will leverage our robust data and infrastructure to develop models that impact millions of users across our three audiences. You will partner cross functionally to set the strategies that help us grow our business and lead efforts to execute those strategies.

You’re excited about this opportunity because you will…

• Lead the effort for growth machine learning: Applying supervised, semi-supervised, active-learning, embedding, and causal inference approaches to improve customer acquisition, retention, resurrection, and development
• Work with the team to build models to optimize promotions, non-monetary interventions, and personalized recommendations across different segments of customers
• Lead and implement end to end ML products, and ship both real time and batch production models via experimentation.
• Use causal inference techniques to find effective approaches to recommend across various segments of customers
• Ship production-grade optimization models
• Exercise variety of techniques to optimize complex systems such as Marketplaces, with domain deep domain knowledge in OR (stochastic optimization, convex optimization, dynamic programming, MIPs, sequential decision models), applied experience with Machine Learning (DL/ NN, Tree Based models,etc.), contextual bandits and reinforcement learning problems
• Collaborate with the team on a wide spectrum of ML techniques.
• You can find out more on our ML blog post here

We’re excited about you because…

• 5+ years of industry experience developing inference and optimization models with business impact — more experience preferred
• 2+ years of experience in a technical management role
• S., or PhD. in Statistics, Computer Science, Electric Engineering, Math, Operations Research, Physics, Economics, or other quantitative field
• Deep understanding of at least one of probability, statistics, machine learning, causal inference, prediction, forecasting, optimization
• Demonstrated familiarity with programming languages e.g. python and machine learning libraries e.g. SciKit Learn, PyTorch/TensorFlow, SQL
• Desire for impact — ready to take on a lot of responsibility and work collaboratively with your team
• Growth-minded — you’re eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
• 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!
• Humble — you’re willing to jump in and you’re open to feedback
• You’re an owner — driven, focused, and quick to take ownership of your work
• 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
• Good understanding of many quantitative disciplines such as statistics, machine learning, operations research, and causal inference

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.

California Pay Range:

$208,000—$282,000 USD