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Home›Jobs›Uber›Applied Scientist II, Safety
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 Scientist II, Safety

Uber • San Francisco, USA

Posted 4d ago🏢 HybridMid-LevelApplied scientist📍 San francisco
Apply Now →

Skills & Technologies

Machine learningA/b testingData analysisCausal inference

Overview

Uber is hiring an Applied Scientist II to join their Safety Science Team, focusing on leveraging analytics and machine learning to enhance platform safety. You'll work on modeling, deep-dive analyses, and experimentation, requiring expertise in machine learning and data analysis.

Job Description

Who you are

You have a strong background in applied science and machine learning, with experience in designing and developing models that deliver measurable impact. You are skilled in conducting deep-dive analyses and causal inference, allowing you to uncover root causes and identify opportunities for improvement. You thrive in cross-functional environments, collaborating with product management, engineering, and operations to drive safety initiatives. You possess a solid understanding of A/B testing methodologies and are comfortable interpreting experimental results to inform product and policy changes. You are passionate about using data to make informed decisions and improve user safety on the platform. You have excellent communication skills, enabling you to present findings effectively to partners and leadership.

Desirable

Experience in the transportation or technology sector is a plus, as is familiarity with safety protocols and standards. A background in statistics or a related field will enhance your ability to conduct rigorous analyses and contribute to high-visibility projects.

What you'll do

In this role, you will own the end-to-end applied science workflow on high visibility projects, starting from problem scoping to delivering insights that drive safety improvements. You will design, develop, and deliver sophisticated machine learning models, ensuring they are robust and have a measurable impact on safety. You will conduct complex analyses to uncover root causes of safety issues and identify high-leverage opportunities for improvement. You will lead the design and interpretation of A/B experiments, rigorously evaluating product and policy changes before they are rolled out on the platform. Your work will directly contribute to making the Uber platform safer for all users, aligning with the company's core value of safety.

What we offer

Uber provides a collaborative work environment where you can grow your skills and make a significant impact. You will have the opportunity to work on high-visibility projects that directly affect user safety. The company values diversity and encourages you to apply even if your experience doesn't match every requirement. You will be part of a team that is committed to leveraging data and analytics to enhance safety across the platform. Uber also offers competitive compensation and benefits, along with a culture that supports work-life balance and professional development.

Interested in this role?

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