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Selected role

Senior Data Scientist, Mobility New Verticals

Uber San Francisco, CA, US

$190k - $211k Senior Full-time

About the Role

Mobility New Verticals is one of the most exciting teams in Uber - here we incubate and grow new ideas, find product market fit, and scale products 0->1->100 (multi-billion dollars in revenue). This unique team is the growth engine of Uber, with the innovation-speed and feel of a startup inside a stable and mature company. We are looking for a Senior Data Scientist to understand long term user behavior to power this growth engine. This is a unique opportunity to model user behavior at the planet scale.

In this role you will serve as a thought leader in understanding the long term business impact of various user experiences and develop LTV and other user growth related models. You will design experiments to validate your models, and incorporate your learnings into business strategy as well as the objective functions that drive the algorithmic outcome of Uber's marketplace systems. This role will need deep expertise in causal modeling, machine learning, consumer LTV modeling and experimentation, as well as a solid understanding of marketplaces and econometrics.

*What the Candidate Will Need / Bonus Points

What the Candidate Will Do**

Prototype and productionize new models and approaches to model customer behavior, with focus on long term impact of consumer actions and experiences by using Uber's planet scale data.
Derive clear and actionable insights from your models and analyses, and communicate them to your stakeholders and business leaders to shape business strategy.
Incorporate models in the broader framework of algorithmic decision making at Uber, influencing millions of outcomes and impacting the lives of millions of Uber users everyday. Collaborate with cross-functional teams such as product, engineering and operations to drive system development end-to-end from conceptualization to final product.

Basic Qualifications

M.S., or Bachelor's degree in Economics, Operations Research, or a related quantitative field (e.g., Statistics, Applied Mathematics, Computer Science with a strong modeling focus).
Mininum 4 years of relevant industry experience as a Data Scientist, Applied Scientist, or equivalent (Mininum 2 years if holding a Ph.D.).
Strong foundations in causal inference, experimental design and econometrics.
Excellent analytical skills, with experience extracting user behavior insights from large datasets.
Knowledge of underlying mathematical foundations of statistics, optimization and economics.
Proficiency with Python for exploratory data analysis and modeling, and modern ML tools such as pytorch, tensorflow etc. Strong ability to communicate with technical and nontechnical audiences.

Preferred Qualifications

Mininum 5 years of relevant industry experience as a Data Scientist, Applied Scientist, or equivalent.
PhD in quantitative fields such as Statistics, Economics, OR, Engineering, Physics, etc.
Proficiency in Python and the modern model development frameworks such as pytorch etc.
Experience in LTV (Life Time Value) modeling, causal inference from observational data and choice modeling.
Experienced in using AI to hypercharge productivity and delivering 10x impact. Exceptional communication skills across technical, non-technical, and executive audiences.

For New York, NY-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 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. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.

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