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Staff Scientist, Tech @ Uber

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 Staff Scientist, Tech

Job Description

Have you ever wondered why it s taking so long for an earner to be matched to your trip, how the price is determined for your trip, or how an earner is picked from the many around youIf so, the Mobility Marketplace Health Science team is for you!
The Marketplace Health Science team at Uber plays a pivotal role in monitoring marketplace performance, detecting issues in real time, and driving solutions through algorithmic and data-driven interventions. Our work is essential to maintaining Uber s market leadership and delivering reliable experiences to riders and earners.
We are seeking experienced data scientists who thrive on solving complex problems at scale. The ideal candidate brings a strong foundation in causal inference, experimentation and analytics, along with a deep understanding of marketplace dynamics and metric trade-offs.
What Youll Do:
  1. Refine ambiguous questions and generate new hypotheses about whether marketplace levers such as Rider and Driver Pricing, Matching, Surge etc are functioning appropriately through a deep understanding of the data, our customers, and our business.
  2. Define how our teams measure success by developing Key Performance Indicators and other user/business metrics, in close partnership with Product and other subject areas such as engineering, operations, and marketing.
  3. Collaborate with applied scientists and engineers to build and improve the availability, integrity, accuracy, and reliability of our models, tables etc.
  4. Design and develop algorithms to increase the speed and accuracy with which we react to marketplace changes.
  5. Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritization of product, growth, and optimization initiatives
What Youll Need:
  1. Undergraduate and/or graduate degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields.
  2. 10+ years of experience as a Data Scientist, Product Analyst, Senior Data Analyst, or other types of data analysis-focused functions.
  3. Deep understanding of core statistical concepts such as hypothesis testing, regression, and causal inference
  4. Advanced SQL expertise.
  5. Experience with either Python or R for data analysis.
  6. Knowledge of experimental design and analysis (A/B, Switchbacks, Synthetic Control, Diff in Diff, etc.).
  7. Experience with exploratory data analysis, statistical analysis and testing, and model development.
  8. Proven track record to wrangle large datasets, extract insights from data, and summarize learnings/takeaways.
  9. Experience with Excel and some dashboarding/data visualization (i.e., Tableau, Mixpanel, Looker, or similar).
Ubers 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 Ubers 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.

Job Classification

Industry: Urban Transport
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Head - Data Science
Employement Type: Full time

Contact Details:

Company: Uber
Location(s): Bengaluru

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Keyskills:   Computer science Data analysis Statistical analysis Senior Data Analyst model development data visualization Monitoring Analytics SQL Python

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Uber

Movement is what we power. Its our lifeblood. It runs through our veins. Its 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 th...