Sr Data Scientist, Tech
Uber
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Job Description
As a Data Science, Tech Lead Manager (TLM), you will play an instrumental role in shaping how Uber tracks its financial data as well as understands and optimizes its financial performance across diverse business lines. You'll work on a wide range of initiatives from building scalable financial data products and developing predictive models to improving reporting workflows and uncovering insights that drive strategic decisions. And you will lead a small team of data scientists partnering closely with teams in Finance and FinTech. This is a hands-on leadership role where you'll balance managing projects and people with diving deep into data yourself.
What You Will Do
- Lead a team of data scientists located in the US and India
- Actively participate and contribute to the technical solutioning and execution of the data science roadmap including helping develop robust forecasting models and impactful Gen AI applications
- Collaborate closely with teams in finance, engineering, product, business analysts, legal and data science teams across different lines of businesses, to design, prototype, and productionize end-to-end data science solutions.
- Develop the team with active coaching and mentoring. Help grow the talent in the team via effective hiring and performance management.
- Deliver strong presentations to stakeholders and senior leadership on the team's work, models, solutions, and data science findings.
Basic Qualifications
- M.S. or Bachelor's degree in Data Science, Computer Science, Statistics, Economics, Mathematics, Finance, or other quantitative fields.
- Minimum 4 years of industry experience as a data scientist with demonstrated ability working with large data sets, mining actionable insights, statistical methods, and basic ML model development
- Domain experience in Finance, Accounting, Payments, FinTech, Tax
- Minimum 1 year of experience managing a small team of Data/Applied Scientists with strong leadership skills, growing and mentoring your team members
- Proficiency in SQL and at least one programming language used for data analysis (e.g., Python or R)
- Experience with data visualization tools (e.g., Tableau, Power BI, Looker or similar)
- Demonstrated ability to translate business problems into analytical solutions and communicate findings to both technical and non-technical audiences
- Strong communication and organizational skills with the ability to manage multiple projects and stakeholders simultaneously.
- Bias to action and proven track record of getting things done.
- Degree or work experience in finance, augmented with work experience as a data scientist (or experience as a data scientist in finance or a related domain) with minimum 1 year of tech leading or managerial experience
- Experience developing forecasting or anomaly detection models, ideally in financial or operational domains
About The Company
Uber
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.
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