Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from DoorDash USA via Indeed
About the Team
Join the team focused on building intelligent, personalized systems that drive fairness, efficiency, and trust in the DoorDash platform. We own the credits and refunds experience—key components of customer satisfaction and retention—and we're pioneering new ways to optimize and personalize these decisions at scale using causal inference and optimization.
About the Role
We're seeking a Machine Learning Engineer to lead the development of state-of-the-art ML systems that personalize and optimize credits and refund decisions. This work is critical to balancing cost efficiency with long-term customer retention and experience.
In this high-impact role, you will partner with cross-functional leaders to design and deploy causal models and optimization algorithms that influence millions of user experiences every week.
You're excited about this opportunity because you will…
- Designing and deploying causal inference models to accurately assess the impact of refunds and credits on customer satisfaction, retention, and behavior
- Developing optimization frameworks that balance customer experience with operational cost, under policy and budget constraints
- Building personalized decision systems that adapt to customer preferences and platform dynamics in real time
- Collaborating with engineering, product, and data science partners to shape the roadmap for trust, service recovery, and consumer experience
- Leading end-to-end model development, including experimentation, deployment, monitoring, and iteration
We're excited about you because you have:
- 3+ years of industry experience delivering machine learning systems with clear business impact, especially in personalization, optimization, or causal inference
- Deep expertise in statistical modeling and causal inference (e.g., uplift modeling, treatment effect estimation, synthetic controls, instrumental variables)
- Experience designing and deploying optimization algorithms (e.g., multi-objective optimization, bandits, constrained optimization)
- Proficiency in Python and ML tooling such as PyTorch, Spark, and MLflow
- A strong product sense and ability to translate business objectives into technical solutions
- M.S. or Ph.D. in a quantitative field (e.g., Computer Science, Statistics, Operations Research, Economics, Mathematics)
- Excellent communication skills and a track record of cross-functional leadership
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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 by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order 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 divers
Source: DoorDash USA careers (Indeed)