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Pay found in job post

Retrieved from the description.

Base pay range

$174,000.00/yr - $193,500.00/yr

Jobs for Humanity is collaborating with Upwardly Global and with Uber to build an inclusive and just employment ecosystem. We support individuals coming from all walks of life.

Company Name: Uber

About the Team Across thousands of storefronts each with thousands of products, Uber Grocery needs to decide exactly what products to show you, how to price them, and how to balance the tricky tradeoffs that come with delivery logistics. We build systems that deeply understand our products, users, and merchants to optimize the marketplace for all parties. Grocery & Retail is one of Uber's biggest new bets. Since launching in 2020, we've achieved an annual run rate of $7 billion in global gross bookings and integrated two strategic acquisitions, Cornershop and Drizly. Our team builds across the end-to-end grocery experience, including consumer growth, fulfillment flows, and catalog management.

What you will do

• Work closely with ML teams to design algorithms and uncover opportunities to improve ranking and personalization.
• Design and analyze large-scale experiments on grocery users in the Eats app to discover insights that improve our discovery platforms.
• Collaborate with Product, Engineering, Design, and other cross-functional partners to understand user behaviors to inform future product strategies.
• Present findings to senior management to inform business decisions.
  
  

Basic Qualifications

• 5+ years of industry experience working in personalization or search
• Experience in algorithm prototyping and development.
• Experience working with funnel optimization, user segmentation, cohort analysis, and lifetime value forecasting.
• Ability to use Python/PySpark for exploratory data analysis and modeling.
• Strong communication skills across technical, non-technical, and executive audiences.
  
  

Preferred Qualifications

• Ph.D., M.S., or Bachelor's degree in Statistics, Economics, Operations Research, or other quantitative fields.
• Experience in a technical leadership role.
• Experience in modern deep learning architectures and probabilistic models.
• Experience in modern generative AI, such as transformer architectures, diffusion models and prompting.
• Experience guiding and mentoring other Scientists.
• Excellent communication skills across technical, non-technical, and executive audiences.
  
  

For New York, NY-based Roles

The base salary range for this role is USD$174,000 per year - USD$193,500 per year.

For San Francisco, CA-based Roles

The base salary range for this role is USD$174,000 per year - USD$193,500 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. You will also be eligible for various benefits. More details can be found at the following link:

Uber is proud to be an Equal Opportunity/Affirmative Action 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. Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Other

• Industries

  Non-profit Organizations

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