Job Description:
The Director will lead the MODS (Marketplace Optimization Data Science) organization, which is the scientific team that embeds in programs throughout Uber to develop the real-time decision, monitoring, and configuration systems which create Uber’s marketplace.
Identifying the need for new MODS teams, and scoping the team size and skill profiles.
Attracting and hiring world-class scientific talent, both team leads and senior ICs
example: we recently made an offer to a Principal Marketplace Designer
Prioritization of hiring needs across MODS
To avoid redundant and competitive hiring efforts, hiring in MODS is done centrally. This means that decisions about allocation will be made by the Director, in consultation with the team leads and candidate, according to need and skill match.
Performance evaluation:
Creating effective data science tracks, competencies, and other performance and leveling criteria
Performance evaluation and leveling of data science managers
Resource allocation:
Working with PMs and EMs to coordinate and allocate data science efforts among the MODS teams.
data science initiatives often start in UberPOOL & UberEverything, and eventually need to be merged with parallel efforts in other groups and upstreamed to Beehive (ex: POOL matching)
upstreaming involves reallocation of resources, and the MODS Director needs to guide effective and timely reallocation
Leadership:
Working with the firstline data science managers (DSMs) to create effective collaboration between data science, engineering, product, and operations.
helping drive alignment between DSMs and the corresponding EMs & PMs
helping identify what aspects of the objectives require data science, and what kind
helping make judgement calls on perfection vs. MVP efficiency
Creating connections between work being conducted in different parts of MODS
Diving deep enough, either technically or logistically, to help guide a struggling team
mentoring the DSMs on effective scientific leadership in product
Requirements
Management skills
Be a leader or former leader of a medium to large (40-person plus) scientific or engineering team
At least 4 years of management experience, and 2 years of IC experience in data science
Track record of hiring, retaining and getting strong results from high-performance scientific teams
Have a track record of leadership successes. Should be able to point to explicit wins with real business impact that they played a strong role in achieving.
Broad quantitative skills, and expertise in some Uber-relevant area
Advanced degree in a relevant scientific field (computer science, statistics, operations research, economics, or similar).
Expertise in one of the key areas for Uber, e.g. forecasting, machine learning, optimization, pricing, experimentation, etc.
Ability to engage with the other key areas for Uber
Skills in data analysis; these do not need to be at the level that an analytics IC would have, but must be enough to understand the needs in this space.
Why? Must be able to:
attract and evaluate scientific talent in a variety of areas, in consultation with team members
scope and prioritize hiring needs across MODS teams
etc.
Applied Science
Bias toward implementation and development of applied mathematics that solve real, immediate product/business needs.
Ability to direct and make judgement calls on perfection vs. MVP efficiency
Employees are given Uber credits every month.
The rare opportunity to change the world such that everyone around you is using the product you built. We’re not just another social web app, we’re moving real people and assets and reinventing transportation and logistics globally.
Sharp, motivated co-workers in a fun office environment.
BENEFITS (U.S.)
401(k) plan, gym reimbursement, nine paid company holidays.
Full medical/dental/vision package to fit your needs.
Unlimited vacation policy; work hard and take time when you need it.
We're bringing Uber to every major city in the world. We need brains and passion to make it happen and to make it happen in style.
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