**What the Candidate Will Need / Bonus Points** \-\-\-\- What the Candidate Will Do ---- You will perform a range of activities to analyze data sources to improve business efficiency & effectiveness and deliver qualitative insights, you will be partnering with engineering/DS/Product teams to build analytics solutions The ideal candidate is experienced working with large data sets and data visualization, as well as being passionate about data and analytics. Following would be what you will do day-to-day: 01. Work independently and with team members to understand database structure and business processes 02. Perform extensive data validation/quality assurance analysis within large datasets 03. Has strong business acumen and think holistically about the business and how analytics fits within the larger vision 04. Prioritise multiple projects, anticipates challenges, remove blockers 05. Deep dive into ambiguous problem statements and uncover hard-to-find trends, synthesize insights to clearly tell the data story 06. Demonstrate high level of accountability 07. Well-versed with a range of techniques (regression, classification, clustering) and processes and internal tools, partner with engineering /product/DS teams 08. Produce write ups with rigor and clearly describe analysis and models 09. Act as a bridge between your team and the data engineering teams, you will ensure that proper data structures / solutions are built to draw insights and its fully validated 10. Get pumped up by deciphering huge data sets and cutting through irrelevant distractions to the heart of the core data questions on bugs 11. Attention to detail, accuracy is a must! \-\-\-\- Basic Qualifications ---- 1. Minimum 5 years experience working in business intelligence, analytics, data engineering, or a similar role 2. Expert knowledge in Python or R and complex SQL queries; experience working with large data sets and Hive database 3. Works independently on problems covering the breadth of the of the problem space 4. Should be a team player and being able to review team’s work 5. Ability to work with remote teams and across time zones 6. Being able to raise the bar for quality/efficiency within the team \-\-\-\- Preferred Qualifications ---- 1. BS / Masters in Maths, statistics, science or any other quantitative discipline 2. Expertise in Statistical Data Analysis , Hypothesis Testing and comfortable with executing A/B experiments 3. Ability to support the team (if needed) on internal ML algorithms 4. Familiarity with Large Language Models (LLMs) and an understanding of how Generative AI can be applied to data-driven solutions We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world 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](mailto:accommodations@uber.com).