Hi, I'm Saurabh Joshi

14/11/2024 - Present

• Winner of Product Hackathon, where our team proposed new Loyalty Points feature based on user wagering and streak progression.
• Designed clickstream funnels to map user journeys, identify drop-offs, and prioritize product improvements.
• Collaborated with cross-functional teams to prioritize and execute ad hoc analyses, aligning product initiatives with business goals.
• Ran experiments on skill-based redirection (beginner → tutorial, skilled → add cash), improving long-term conversions by 10%.
• Evaluated RummyCom lobby revamp and trust & safety features via A/B tests, showing measurable conversion, cash games and retention uplift.
• Developed an I2R pipeline using Spark SQL to surface onboarding frictions, which helped identify product gaps and improve new user funnel visibility.
• Led a Default Entry Fee recommendation A/B experiment where users were shown tailored table suggestions, improving AWPU by 6%, average entry fee by 4%, and games played by 2%.

06/07/2024 - 12/11/2024

• Developed a Python script to extract millions of data using Kibana API, analyzing ad-code / ad-type mappings, which resulted in identifying key optimization areas.
• Collaborated with Product Managers to optimize real-time bidding (RTB) parameters, improving ad placement efficiency and increasing coverage by 46%.
• Automated campaign performance reporting (Python + Airflow), reducing manual work by 98% and enabling a 2x increase in campaign launches.
• Built and optimized product data pipelines in SQL/Big Query, improving reporting reliability for daily usage stats and P&L dashboards.
• Identified high-value keyword opportunities through SQL analysis, driving a 16% increase in keyword utilization and a 45% gross profit uplift.
• Built and optimized a data pipeline for the Internal Crawler product using SparkSQL, delivering daily usage statistics and improving reporting reliability.
• Supporting with Daily Reports to share Product P&L to the CEO and stakeholders.
• Worked with Tableau to create multiple dashboards to find profitable campaign patterns to optimize and drive better results.
• Shipped a 0 to 1 Article Subtitle Feature across all domains, and delivered new websites to Campaign Managers and Partner Teams.
• Collaborated with Tech/Design teams to solve data/site/UI issues.

01/10/2021 - Present

• Designed data marts for user retention, feature adoption, and marketing impact using SQL, MongoDB, and Python.
• Designed and created web scraping data pipelines for publicly available data as per various use-cases
• Designed and implemented scalable ETL pipelines using CGP services including Dataproc, Cloud Storage, Bigtable, Big Query, Pub/Sub, and Cloud Composer, enabling efficient data ingestion, transformation, and querying of large datasets across multiple systems.
• Built 300+ dbt models with automated data validation tests, version-controlled documentation, and reusable Jinja macros for clean, modular code.
• Implemented CI/CD pipelines for data transformations, ensuring code quality and reducing deployment times by 60%.
• Collaborated with clients including Yahoo, Ellequant, buidlerstribe (buidl.so), and Klimaticz and many more on various data projects, delivering actionable insights and process improvements.
• Skills: PySpark, Docker, Google Cloud Platform, Streamlit, Airflow, dbt, SQL, Python, data modeling, CI/CD, Product Analytics.

01/06/2021 - 31/07/2021

Responsible for developing CURD API using NodeJS integrating with PostgreSQL database.

01/03/2021 - 31/06/2021

• I developed a Standalone database prospect search engine tool for Georgia Tech University as a Data Analyst Intern.
• Implemented a Web Sports Analytics dashboard application to analyze players’ game data and track player sentiments, tweet comparison and overall standings between players, resulting in a 10% increase in player performance and a 5% increase in player recruitment.