Data Scientist (Product Analytics)

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

Scope & Impact: You will have the opportunity to collaborate with multiple cross-functional global teams to deliver scalable data solutions wherein the expectation is to ->

1. Build scalable analytical frameworks to support product analytics for Uber's Customer Obsession Platform
2. Be an invaluable partner to product managers, engineers, operations, & various data teams to help create and execute the direction of the product roadmap which includes scoping the business problem, providing a data lens to product design, owning the experimentation cycle to full global rollouts and eventually impact estimation & long term monitoring.
3. Proactively communicate insights and drive projects to drive towards team goals
4. Ensure data quality across critical pipelines and to set up processes to triage data issues
5. Build & maintain critical data pipelines, insight boards & monitoring tools that help track metrics to measure and monitor platform health
6. Seek out opportunities to build new solutions to tackle Customer & Business pain points

---- Basic Qualifications ---

1. -2+ years of work experience with a Bachelor's Degree OR 1+ years of work experience with a Master's Degree. Work experience should be in a data-focused role such as product analytics, risk analytics, business analytics, business operations, or data scienc
2. eEducation in Engineering, Computer Science, Math, Economics, Statistics, Operation Research or equivalent experienc
3. eProven competency in statistical languages like SQL, SAS, R and/or in modern programming languages like Pytho
4. nPast experience with a Product / Tech / Analytics Services company serving businesses with millions of customers on multiple platforms and countries

---- Preferred Qualifications --

1. --SQL mastery. Write efficient and complex code in S
2. QLExperience in Python/R, Experimentation methods like A/B testing, and Statistical modelling is preferr
3. edExperience in Customer Service related domains with a Product / Technology / Analytics Services company is a pl
4. usProven ability to handle and visualise large datasets, explore and utilise raw data fee
5. dsLove of data - One should have the zeal to just go get the required data and turn it into an insightful sto
6. ryAbility to build a structured approach to problem-solving that leads to high quality hypothes
7. esStrong sense of ownership, accountability, and entrepreneurial spir
8. itEffective communicator & proactive collaborat
9. orIndependent & autonomous, while still a strong team play
10. erEnthusiastic, self-starting and thrives in changing, agile environments