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About the Role
- We are looking for a highly driven and experienced Data Scientist to join Uber's Fin Tech
- Data Science team. In this role, you will have the amazing opportunity to shape how Uber understands and optimizes its financial performance across diverse business lines. You'll partner closely with Data Science, Product, Engineering, Finance, and other cross-functional stakeholders on fast-moving, high-stakes problems. A deep analytical and science passion and the ability to execute key business priorities are a must for this role. Your performance is measured by the insights you give, communication effectiveness, and the initiative to drive ideas and implement them into action!
What the Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----
- Analyze large volumes of financial and operational data to extract actionable insights, with a focus on key financial and business metrics
- Develop models to forecast financial metrics, detect anomalies, and support strategic decision-making across Uber's financial systems.
- Partner with stakeholders across Finance, Product, Engineering, and ML teams to design, prototype, and productionize end-to-end data science solutions.
- Build end-to-end data pipelines and self-serving dashboards. Automate whatever you can!
- Communicate your findings to cross-functional peers and management.
- Build tools and documentation that enable operational teams to independently explore financial metrics and monitor key performance indicators.
- Investigate and resolve discrepancies across multiple financial systems and datasets, ensuring consistency and trust in reported metrics
- Build effective visualizations to communicate data to key decision-makers
- Get a deep understanding of the Fin Tech systems and data flows involved; document and train internal personnel to institutionalize the learnings of the data science practice.
---- Basic Qualifications ----
- Bachelor's degree with 2+ years, or Master's degree with 1+ years, of relevant industry experience in Data Science or similar roles.
- Advanced SQL proficiency and strong understanding of data modeling.
- Solid foundation in statistical methods and data exploration techniques.
- Experience building dashboards or visualizations using Tableau, Plotly, Looker, or similar platforms.
- Strong communication skills, with the ability to translate data findings into clear recommendations to cross-functional stakeholders
---- Preferred Qualifications ----
- Experience in Python/R for data analysis, modeling, and pipeline automation.
- Experience developing forecasting or anomaly detection models, ideally in financial or operational domains
- Demonstrated ability to decompose complex business problems into structured analytical approaches
- Proven success in cross-functional collaboration and stakeholder engagement.
- Prior exposure to finance or related industries is a plus
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuelds progress. What moves us, moves the world - let's move it forward, together.
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.
Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.
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About Uber
Reviews
3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
45%
Recommend to a Friend
Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Scientist L3
0 reports
$145,456
total / year
Base
-
Stock
-
Bonus
-
$123,638
$167,274
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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