About the Role

As a member of the GSS DAS team, you will have the opportunity to drive the analysis behind various Product and Ops related decisions at Uber. You will perform a range of activities demonstrating your & analytical thought leadership andautomation mindset, andwill be involved in leading multiple data-driven projects including , but not limited to :

1. Doing strategic & technical program management across different pillars of Uber's lines of businesses
2. Design of KPI tracking systems for complex company-wide metrics across various Uber products and teams globally
3. Performing analytical deep dives to drive product/strategy road-map
4. Engineer scalable data ingestion frameworks and optimized analytical layers that mirror real-time product lifecycles, ensuring data integrity across high-volume environments.

Development of Machine Learning based solutions:

1. Building scalable automation tools using python & AI

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

You will work on a range of analytics projects to help partner teams in boosting efficiency and fostering growth throughout the business. Your role will entail delivering valuable qualitative insights and collaborating with engineering, data science, and product teams to develop analytics solutions.

The ideal candidate is experienced working with large data sets, automations and data visualization, as well as being passionate about data analytics and automations.

Following would be what you will do day-to-day:

1. Utilize expertise in data analysis and visualization to develop end-to-end analytical solutions.
2. Translate analytical solution into actionable insights and recommendations for technical and non-technical audience in a clear, concise and persuasive way
3. Maintain and continue to raise the bar for quality/efficiency of analytical solution delivery
4. Focus on long term improvements by building, maintaining, and documenting best practices within the team and seek continuous improvement opportunities
5. Lead vendor data analysts in project execution
6. Do all that it takes to drive and deliver multiple analytical and data engineering projects to partner teams across Uber
7. Get pumped up by deciphering huge data sets and cutting through irrelevant distractions to the heart of the core data questions from partner teams
8. Attention to detail, accuracy is a must!
9. Humble and scrappy - willing to take on tactical work when it helps unblock the team.
10. Design ML-based project plans/strategies and translate stakeholder requirements into technical model blueprints and evaluation criteria. Lead the transition from business problem to technical solution by defining model scope, data requirements, and success benchmarks.
11. Having hands on experience in Integrating LLMs (like GPT) into apps while accessing open source or paid APIs using python
12. Developintelligent data products(e.g., chatbots, recommendation systems)
13. Applying pre-trained models to business use cases

---- Basic Qualifications ----

1. Minimum 7 years experience working in business intelligence, analytics, data engineering, or a similar role
2. Experience using SQL in a production environment.
3. Experience using Python or R to work with large data sets at scale and apply ML/DL/AI capabilities to build scalable solutions
4. Experience with dashboarding and using data visualization tools.
5. Fluency in communicating data insights (Methods, Results & Actions) with the peer group
6. Should be a team player and being able to multitask
7. Ability to work with remote teams and across time zones
8. Being able to raise the bar for quality/efficiency within the team

---- Preferred Qualifications ----

1. BS / MS degree equivalent experience in Statistics, Economics, Engineering, or other quantitative fields.
2. Experience in experimental design and analysis, exploratory data analysis, data modelling and statistical analysis.
3. Experience managing projects across large, ambiguous scopes and driving initiatives in a fast moving, cross-functional environment.
4. Experience working with Product and Engineering teams

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 accommodations@uber.com.