Job Description

About the Role

The BizOps team is the Ops owner for building scalable analytical products & processes while providing deep science & insighting to Uber's hardest problems while creating scalable value for Uber. This role is on the ground floor of a newly formed Business Operations team in APAC Central Operations with a goal of unlocking the best advanced analytics and insights, save thousands of hours via build for scale automation, #FindTheMoney via economic performance interventions and incubate + scale GenAI based tools in APAC. This role within the BizOps team will focus on enabling data-driven decision-making by ensuring the reliability and accessibility of organizational data and lies at the intersection of engineering, analytics, and product development, focusing on creating impactful analytical products.




What the Candidate Will Do:


Collaborate closely with local operations teams and global XFN stakeholders to build the highest quality analytical products and data sources Implement incremental improvements to data pipelines by optimizing Presto SQL queries, parallelizing data jobs, and reducing computational overhead in complex ELT processes. Own new product experimentation including plan creation, roll-out, and monitoring Develop and track metrics and reporting functions to measure and monitor risk products on our platform Document pipeline architectures and maintain version-controlled codebases following engineering best practices (continuous integration and continuous delivery, unit tests, code documentation, and more). Audit existing analytical products to resolve discrepancies in metric definitions across organizations and teams (e.g., aligning "active users" calculations between operations and finance teams). Build and maintain operational and critical analytical products that help monitor and diagnose complex metrics for diverse teams.


Basic Qualifications:


5+ years of experience in a data-focused role such as product analytics, business analytics, business operations, or data science Education in Engineering, Computer Science, Math, Economics, Statistics or equivalent experience Experience in modern programming languages (Matlab, Python) or statistical languages (SQL, SAS, R) Past experience with a Product / Tech company serving millions of customers on multiple platforms and countries


Preferred Qualifications:


SQL mastery. Write efficient and complex code in SQL Experience in Python/R and experimentation, A/B testing, and statistical modelling Proven ability to handle and visualise large datasets, explore and utilize raw data feeds Love of data - you just go get the data you need and turn it into an insightful story. A well-organized, structured approach to problem-solving Strong sense of ownership, accountability, and entrepreneurial spirit Great communicator, problem-solver & confident in decision making Independent & autonomous, while still a strong teammate * Enthusiastic, self-starting and thrives in changing, agile environments