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Home›Jobs›Uber›Applied Machine Learning Scientist, Payments
Uber

About Uber

Reimagining transportation for a better world

🏢 Tech👥 1001+ employees📅 Founded 2009📍 Mission Bay, San Francisco, CA💰 $15.8b⭐ 3.9
B2CTravelMarketplaceTransportRidesharingDelivery

Key Highlights

  • Public company (NYSE: UBER) since May 2019
  • Completed over 1.5 billion trips globally
  • Generated $4.8B in revenue from Uber Eats in 2020
  • Raised $15.8 billion in funding

Uber Technologies, Inc. (NYSE: UBER) is a leading ride-hailing platform headquartered in Mission Bay, San Francisco, CA. Founded in 2009, Uber has transformed transportation services, completing over 1.5 billion trips globally. The company went public in May 2019 and has raised $15.8 billion in fund...

🎁 Benefits

Uber provides comprehensive healthcare, a robust employee stock purchase plan, generous paid vacation, and a four-week sabbatical after five years of ...

🌟 Culture

Uber fosters a culture of innovation and adaptability, continuously expanding its services beyond traditional ride-hailing. The company emphasizes wor...

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Uber

Applied Machine Learning Scientist, Payments

Uber • Hyderabad, IND

Posted 2 months ago🏛️ On-SiteMid-LevelMachine learning engineer📍 Hyderabad
Apply Now →

Skills & Technologies

PythonSQLPysparkMachine learningStatisticsOptimization

Job Description

**About the Role** We are looking for a Machine Learning Scientist to join our Payments Machine Learning team and make meaningful contributions to our mission to streamline and optimize Uber’s global payment experiences. In this role, you will be able to use your strong quantitative skills in the fields of machine learning, statistics, economics, operations research to improve the Uber Payments experience. Example projects we work on include optimizing transaction routing and automated retry strategies to improve payment authorization success rates and rider/eater conversion. We are looking for experienced candidates with a passion for solving new and difficult problems with data. In this role, you will be able to use your strong quantitative skills in the fields of machine learning, statistics, economics, operations research to improve the Uber Payments experience. \-\-\-\- What the Candidate Will Do ---- 1. Design, build, deploy machine learning, statistical, optimization models into Uber production systems for a wide range of applications. 2. Collaborate with multi-functional teams across areas such as product, engineering, operations, and design to drive system development end-to-end from conceptualisation to productionization. 3. Understanding product performance and to find opportunities within data. \-\-\-\- Basic Qualifications ---- 1. 3+ years of proven experience as a Machine Learning Scientist, Machine Learning Engineer, Research Scientist or equivalent. 2. Experience in production coding and deploying ML, statistical, optimization models in real-time systems. 3. Ability to use Python or other programming languages to work efficiently at scale with large data sets in production systems. 4. Proficiency in SQL, PySpark. \-\-\-\- Preferred Qualifications ---- 1. Experience in the Fintech / Payments industry 2. Excellent communications skills in a cross-functional setting. 3. Thought leadership to drive multi-functional projects from conceptualisation to productionization. 4. Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability. 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](mailto:accommodations@uber.com).

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