Suraj Singh

• Developed and maintained Looker Studio (GDS)/Quick BI/Tableau dashboards to deliver actionable insights and enable data-driven decision-making across business units.
• Led dashboard automation initiatives using Python and SQL, significantly improving the efficiency of data visualization and reporting workflows.
• Worked with cross-functional stakeholders to fulfill ad-hoc analytical requests and provide timely insights aligned with business goals.
• Worked closely with Decision Scientists and Data Scientists to evaluate model performance, debug experiment design issues, to address concerns such as metric misalignment, bias detection, and tracking accuracy to ensure robust and reliable experiment outcomes, and support product experimentation initiatives.
• Engaged with cross-functional stakeholders to translate experimental insights into actionable business strategies, directly improving product adoption and customer engagement.
• Developed tracking mechanisms to connect user journeys across the funnel, enabling a holistic view of initiative effectiveness.

Key Projects:

• Faster Delivery Mode: Worked on the experimentation and tracking of a premium offering targeting time-sensitive, high-paying customers. Specifically led the product tracking across layers by defining success/guardrail metrics for better understanding of the product performance.
• Economical Delivery Mode: Designed strategies to engage cost-sensitive customers by highlighting longer delivery times in exchange for reduced pricing, and leveraged customer behavioral data to optimize adoption.
• Flash Product Launch: Conducted customer base sizing and heuristic behavioral analysis for a new ultra-fast delivery mode; applied geographical and hotspot mapping techniques to deliver the initial launch sizing. Also, conducted several experiments in the chosen hotspot regions to drive the growth and penetration.

Tools & Technologies: Python, SQL(BQ & MC), Looker Studio, Litmus/Eppo (Experimentation)

• Conducted performance analysis for Uber for Business (U4B), developed business and product metrics for SMB, Mid-Market, and Enterprise-level organizations across Asia, Middle East, Japan, Australia, and the USA.
• Queried large-scale datasets using Presto and BigQuery, and leveraged Python for advanced analysis to support day-to-day business operations.
• Developed and maintained complex dashboards using Looker Studio (GDS), enabling stakeholders to track real-time operational and financial performance across Uber Health, Central, and Rides teams.
• Built automation tools and internal web interfaces using Python to streamline recurring tasks, saving the team over 80 hours of manual effort per week.

Tools & Technologies: Python, SQL (Presto, BigQuery), Looker Studio, Automation, Stats/ML

• Conducted in-depth market and product research using global datasets, supporting new product development through concept testing and rapid prototyping.
• Utilized BigQuery and Python to analyze market trends and customer behavior, generating actionable insights and hypotheses for strategic decision-making.
• Created dashboards and visual reports in Looker to effectively communicate findings to marketing, sales, and product stakeholders.
• Collaborated with cross-functional teams to define data-driven product requirements, ensuring solutions aligned with both market demand and operational feasibility.

• Analyzed and interpreted large volumes of technical data including product specs, test results, and customer feedback to uncover trends and recommend product improvements.
• Built and maintained dashboards in Looker to support bidding strategies and financial analysis of year-over-year sales and product performance.
• Conducted statistical analysis of testing datasets using Python to refine product definitions, optimize performance parameters, and support R&D efforts.
• Worked with cross-functional teams to deliver timely, goal-aligned insights on ad-hoc analytical requests.
• Key Projects and Responsibilities: