Sr Manager, Applied Science
Uber Eats
San Francisco, California
Posted yesterday
Responsibilities
Primary Duties
- Translate Business to Science: Turn ambiguous business challenges into crisp scientific roadmaps, structured experiment plans, and actionable analytical frameworks.
- Build the Experimentation Stack: Lead our core measurement engine. Build and scale geo-experiments, conversion lift studies, and synthetic controls to establish the scientific 'ground truth' for marketing efficiency.
- Triangulate Measurement: Complement experimental lift with Marketing Mix Modeling (MMM) and multi-touch/algorithmic attribution, calibrating observational models directly against experimental results.
- Scale & Lead Scientists: Coach, elevate, and inspire a team of Applied Scientists (L4–L5+), setting a high bar for scientific rigor, execution speed, and business impact.
- Drive AI & ML Innovation: Integrate modern AI, predictive ML, and LTV modeling into production systems to optimize budget allocation and automated decision-making.
- Stakeholder Management & Execution: Serve as the core scientific partner to Marketing, Media, Ops, and Engineering leaders across Mobility and Delivery, translating complex statistical methodologies into actionable decision frameworks.
Experience Requirements
Required
7+ years of experience in Applied Science, Quantitative Research, or Machine Learning in tech or ad-tech. 3+ years of direct people management experience building and leading science teams.
7 years of experience
Benefits & Perks
Benefits Package
- participate in Uber's bonus program
- may be offered an equity award
- eligible for various benefits
- eligible to participate in a 401(k) plan
Required Skills
Technical Skills
proficiency in Pythonproficiency in SQLproficiency in modern AI/ML frameworksproficiency in big data technology
Soft Skills
exceptional executive communication skills
Full Job Description
Senior Manager Of Applied Science
Uber's Marketing team invests hundreds of millions globally to grow our Mobility and Delivery platforms. We are looking for an experienced Senior Manager of Applied Science to lead strategic measurement and quantify the true impact of our marketing investments.
In this role, you will lead a high-performing team of Applied Scientists working at the intersection of causal inference, machine learning, modern AI, and marketing technology. Partnering directly with Marketing, Media, Operations, and Engineering, you will build and deploy Uber's next-generation marketing science stack—shaping multi-million dollar decisions in real time across our global business.
Responsibilities
Requirements
Preferred Qualifications
For New York City, NY-based roles: The base salary range for this role is USD $252,000 per year - USD $280,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $252,000 per year - USD $280,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Uber's Marketing team invests hundreds of millions globally to grow our Mobility and Delivery platforms. We are looking for an experienced Senior Manager of Applied Science to lead strategic measurement and quantify the true impact of our marketing investments.
In this role, you will lead a high-performing team of Applied Scientists working at the intersection of causal inference, machine learning, modern AI, and marketing technology. Partnering directly with Marketing, Media, Operations, and Engineering, you will build and deploy Uber's next-generation marketing science stack—shaping multi-million dollar decisions in real time across our global business.
Responsibilities
- Translate Business to Science: Turn ambiguous business challenges into crisp scientific roadmaps, structured experiment plans, and actionable analytical frameworks.
- Build the Experimentation Stack: Lead our core measurement engine. Build and scale geo-experiments, conversion lift studies, and synthetic controls to establish the scientific "ground truth" for marketing efficiency.
- Triangulate Measurement: Complement experimental lift with Marketing Mix Modeling (MMM) and multi-touch/algorithmic attribution, calibrating observational models directly against experimental results.
- Scale & Lead Scientists: Coach, elevate, and inspire a team of Applied Scientists (L4–L5+), setting a high bar for scientific rigor, execution speed, and business impact.
- Drive AI & ML Innovation: Integrate modern AI, predictive ML, and LTV modeling into production systems to optimize budget allocation and automated decision-making.
- Stakeholder Management & Execution: Serve as the core scientific partner to Marketing, Media, Ops, and Engineering leaders across Mobility and Delivery, translating complex statistical methodologies into actionable decision frameworks.
Requirements
- 7+ years of experience in Applied Science, Quantitative Research, or Machine Learning in tech or ad-tech.
- 3+ years of direct people management experience building and leading science teams.
- Exceptional executive communication skills—able to make complex statistical concepts intuitive for business and executive stakeholders.
- Demonstrated track record of translating broad business objectives into concrete scientific strategy and technical deliverables.
- Deep expertise in causal inference and experimentation at scale (e.g., geo-experiments, conversion lift, synthetic controls, quasi-experiments).
- Strong foundation in machine learning, predictive modeling, and applied AI in enterprise environments.
- Proficiency in Python, SQL, modern AI/ML frameworks, and big data technology.
Preferred Qualifications
- Ph.D. or M.S. in Statistics, Econometrics, Economics, Computer Science, Machine Learning, Operations Research, or a related quantitative field.
- 5+ years of domain experience in AdTech/MarTech, media optimization, and digital ad platforms (e.g., Meta, Google, TikTok, Programmatic).
- Proven experience scaling automated geo-testing engines or custom conversion lift frameworks across complex media channels.
- Hands-on experience using experimental ground truth to calibrate tools like Marketing Mix Models (MMM) and attribution algorithms.
For New York City, NY-based roles: The base salary range for this role is USD $252,000 per year - USD $280,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $252,000 per year - USD $280,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
How to Apply
$100
/ hour
Uber Eats pays $100 for General Manager in San Francisco, California, with most salaries ranging from $59 to $169. Pay can vary based on role, experience, and local cost of living.
Median
$100
Low
$59
High
$169
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Figures represent approximate ranges and may vary based on experience, location, and other factors. For the most accurate information, please consult the employer directly. Contact us to suggest updates to this information.





