What are the responsibilities and job description for the Applied Scientist II, Measurement Systems position at Karkidi?
About the Role
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We seek an experienced Applied Scientist to join the eXperimentation, Personalization, and Optimization team (XPO). In this role, you'll work closely with various cross-functional teams (marketing managers, engineers, product managers, operations, data scientists, and analysts) to help optimize Uber’s marketing practices. The XPO team lives at the intersection of economics, statistics, and computer science. An ideal candidate has a demonstrable ability to successfully apply rigorous scientific methods (experimental design, media mix modeling, causal inference, or machine learning model development & deployment) to messy real-world problems.
What the Candidate Will Do
- Perform various analyses, hypothesis testing, and causal inference to statistically assess the relative impact and extract trends.
- Build and deploy ML models to enhance understanding of user behavior and predict future performance of marketing campaigns.
- Design experiments and interpret the results to draw detailed and measurable conclusions.
- Present findings to senior management to inform business decisions.
- Collaborate with cross-functional teams across data science, product, engineering, operations, and marketing.
Basic Qualifications
Preferred Qualifications
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 compensation. You will also be eligible for various benefits.
Uber is proud to be an Equal Opportunity / Affirmative Action 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.
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.
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