Scientist II

Job Description

he Core Analytics & Science Team (CAS) is Uber's primary science organisation, covering both our main lines of business as well as the underlying platform technologies on which those businesses are built. We are a key part of Uber's cross-functional product development teams, helping to drive every stage of product development through data analytic, statistical, and algorithmic expertise. CAS owns the experience and algorithms powering Uber's global Mobility and Delivery products. We optimise and personalise the rider experience, target incentives and introduce customizations for routing and matching for products and use cases that go beyond the core Uber capabilities.

---- What You Will Do ----

Refine ambiguous questions and generate new hypotheses and design ML based solutions that benefit product through a deep understanding of the data, our customers, and our business

Deliver end-to-end solutions rather than algorithms, working closely with the engineers on the team to productionize, scale, and deploy models world-wide.

Use statistical techniques to measure success, develop northstar metrics and KPIs to help provide a more rigorous data-driven approach in close partnership with Product and other subject areas such as engineering, operations and marketing

Design experiments and interpret the results to draw detailed and impactful conclusions.

Collaborate with data scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines.

Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritisation of product, growth, and optimisation initiatives.

Present findings to senior leadership to drive business decisions

---- What You Will Need ----

1. Undergraduate and/or graduate degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields.
2. 4+ years experience as a Data Scientist, Machine learning engineer, or other types of data science-focused functions
3. Knowledge of underlying mathematical foundations of machine learning, statistics, optimization, economics, and analytics
4. Hands-on experience building and deployment ML models
5. Ability to use a language like Python or R to work efficiently at scale with large data sets
6. Significant experience in setting up and evaluation of complex experiments
7. Experience with exploratory data analysis, statistical analysis and testing, and model development
8. Knowledge in modern machine learning techniques applicable to marketplace, platforms
9. Proficiency in technologies in one or more of the following: SQL, Spark, Hadoop

---- Preferred Qualifications ----

1. Advanced SQL expertise
2. Proven track record to wrangle large datasets, extract insights from data, and summarise learnings/takeaways.
3. Proven aptitude toward Data Storytelling and Root Cause Analysis using data
4. Advanced understanding of statistics, causal inference, and machine learning
5. Experience designing and analyzing large scale online experiments
6. Ability to deliver on tight timelines and prioritise multiple tasks while maintaining quality and detail
7. Ability to work in a self-guided manner
8. Ability to mentor, coach and develop junior team members
9. Superb communication and organisation skills

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 .