메인 콘텐츠로 건너뛰기

Data Science II, InsurTech

Data Scientist, Data Science
San Francisco, California |
Sunnyvale, California
Full Time

About the Role

We're looking for a data scientist to join our InsurTech Data Science team under Core Services to provide data expertise as we work to make this world a safer place to move around.

This is a cross-functional role within a global team that will work closely with product management, safety operations, engineering, and partner data teams. The work has a global scope, with different cultural and regional aspects considered for each of the studies.

Uber's Stand for Safety value shows the importance and relevance of Safety here:

"We embed safety into everything we do. Our relentless pursuit to make Uber safer for everyone using our platform will continue to make us the industry leader for safety. We know the work of safety never stops, yet we can and will challenge ourselves to always be better for the communities we serve."

What the Candidate Will Need

---- What the Candidate Will Do ----

The InsurTech Science team applies data science and analytics to insurance initiatives from delivering the best auto crash reporting experience to ensuring the most accurate claims handling process. As a member of the team you will conduct deep-dive analyses, design and analyze experiments, lead projects end-to-end, and support the development of machine learning models to make our platform as safe as possible for all users. You will play an influential role in driving critical products and policy decisions.

---- Basic Qualifications ----

  1. M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields
  2. Advanced proficiency in SQL
  3. Proficiency with Python or R
  4. Familiarity with experimental design (e.g., A/B experiments) and statistical methods
  5. Experience with dashboarding and data visualization tools such as Tableau, Looker or similar

---- Preferred Qualifications ----

  1. Exceptional judgment, critical-thinking, and decision-making skills
  2. Advanced degree or similar in Mathematics, Statistics, Computer Science, Economics
  3. Ability and experience in extracting insights from data, and summarizing findings / takeaways
  4. End to end experience with product analytics and experimentation
  5. 4+ years of Python or R experience
  6. 4+ years of SQL experience
  7. Experience with Data Pipeline/ETL creation
  8. Ability to identify stakeholders, build relationships, and influence others to get work done
  9. Strong ability to document research and analysis

For San Francisco, CA-based roles: The base salary range for this role is USD$142,000 per year - USD$158,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$142,000 per year - USD$158,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

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 fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

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.


See our Candidate Privacy Statement

Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran Status, or any other characteristic protected by law.

선호하는 언어 선택

아랍어, العربية아삼어, অসমীয়া아제르바이잔어, Azərbaycanca불가리아어, Български벵골어, বাংলা카탈로니아어(스페인), Català (Espanya)체코어, Čeština덴마크어, Dansk독일어, Deutsch그리스어, Ελληνικά영어, English스페인어, Español (Internacional)스페인어, Español (Argentina)스페인어, Español (Chile)스페인어, Español (Colombia)스페인어, Español (Costa Rica)스페인어(유럽), Castellano스페인어, Español (Honduras)스페인어, Español (México)스페인어, Español (Uruguay)에스토니아어, Eesti핀란드어, Suomi프랑스어(캐나다), Français (Canada)프랑스어, Français (France)히브리어, עברית힌디어, हिन्दी크로아티아어, Hrvatski헝가리어, Magyar인도네시아어, Bahasa Indonesia이탈리아어, Italiano일본어, 日本語조지아어, ქართული칸나다어, ಕನ್ನಡ한국어, 한국어쿠르드어, کوردی리투아니아어, Lietuvių라트비아어, Latviešu말라얄람어, മലയാളം마라티어, मराठी노르웨이어(보크말), Norsk Bokmål네팔어, नेपाली네덜란드어, Nederlands펀잡어, ਪੰਜਾਬੀ폴란드어, Polski포르투갈어(브라질), Português (Brasil)포르투갈어(유럽), Português (Portugal)루마니아어, Română러시아어, Русский싱할라어(스리랑카), සිංහල슬로바키아어, Slovenčina슬로베니아어(슬로베니아), Slovenščina스웨덴어, Svenska스와힐리어, Kiswahili타밀어, தமிழ்텔루구어, తెలుగు태국어, ไทย터키어, Türkçe우크라이나어, Українська우르두어, اردو베트남어, Tiếng Việt중국어, 简体中文중국어(홍콩[중국 특별행정구]), 香港中文중국어(대만), 繁體中文

선호하는 언어 선택

아랍어, العربية아삼어, অসমীয়া아제르바이잔어, Azərbaycanca불가리아어, Български벵골어, বাংলা카탈로니아어(스페인), Català (Espanya)체코어, Čeština덴마크어, Dansk독일어, Deutsch그리스어, Ελληνικά영어, English스페인어, Español (Internacional)스페인어, Español (Argentina)스페인어, Español (Chile)스페인어, Español (Colombia)스페인어, Español (Costa Rica)스페인어(유럽), Castellano스페인어, Español (Honduras)스페인어, Español (México)스페인어, Español (Uruguay)에스토니아어, Eesti핀란드어, Suomi프랑스어(캐나다), Français (Canada)프랑스어, Français (France)히브리어, עברית힌디어, हिन्दी크로아티아어, Hrvatski헝가리어, Magyar인도네시아어, Bahasa Indonesia이탈리아어, Italiano일본어, 日本語조지아어, ქართული칸나다어, ಕನ್ನಡ한국어, 한국어쿠르드어, کوردی리투아니아어, Lietuvių라트비아어, Latviešu말라얄람어, മലയാളം마라티어, मराठी노르웨이어(보크말), Norsk Bokmål네팔어, नेपाली네덜란드어, Nederlands펀잡어, ਪੰਜਾਬੀ폴란드어, Polski포르투갈어(브라질), Português (Brasil)포르투갈어(유럽), Português (Portugal)루마니아어, Română러시아어, Русский싱할라어(스리랑카), සිංහල슬로바키아어, Slovenčina슬로베니아어(슬로베니아), Slovenščina스웨덴어, Svenska스와힐리어, Kiswahili타밀어, தமிழ்텔루구어, తెలుగు태국어, ไทย터키어, Türkçe우크라이나어, Українська우르두어, اردو베트남어, Tiếng Việt중국어, 简体中文중국어(홍콩[중국 특별행정구]), 香港中文중국어(대만), 繁體中文