Dec 2022 – May 2024 · 1 yr 5 mos · United States · Remote

• Spearheaded the development of a proprietary data-driven product aimed at identifying high-performing doctors within the healthcare system, resulting in a projected cost savings of $100+ Million annually across clients
• Deployed product into production environment, monitoring its performance to ensure its effectiveness and relevance
• Utilized advanced statistical testing methodology and machine learning algorithms to extract insights from complex datasets, including patient outcomes, treatment effectiveness, and physician performance metrics
• Designed and implemented data preprocessing pipelines to clean, transform, and standardize heterogeneous data sources, ensuring data quality and consistency, resulting in a reduction of data processing efforts
• Collaborated closely with cross-functional teams including software engineers, domain experts, and healthcare professionals to gather requirements, iterate on prototypes, and deploy the final product
• Led the development of a sophisticated data analytics project aimed at quantifying the financial impact of identifying high-performing doctors within a healthcare system
• Conducted thorough validation and sensitivity analysis to assess the robustness of the financial estimates, providing stakeholders with a clear understanding of the confidence level associated with the projected savings
• Developed new metrics and methodology to identify the impact of the product for each plan sponsor by creating self-service dashboards
• Developed robust methodologies for evaluating and relevance of new data sources, considering factors such as data quality, availability, and alignment with business objectives, informing decisions regarding data acquisition and integration

Apr 2021 – Dec 2022 · 1 yr 8 mos · United States

• Reduced the at-risk revenue by ~$2M by identifying key factors responsible for client retention using tree based methods and providing account managers with actionable insights
• Saved over $30k in monthly testing costs by improving web scraping performance against anti-bot technology by identifying causal relationships between factors responsible for blocking using A/B testing
• Enabled 60% faster issue detection by transitioning the script development process from pull to push-based by providing a predictive maintenance solution using clustering (K-Means) and classification (XGBoost) models
• Increased engagement by 12% on QL2’s product platform by creating features around pricing strategies - frequency and magnitude of changes, data aggregations, and creating automated alerting systems for actionable insights
• Lead the analytics team to create a framework for generating content for the social media to establish QL2 as a thought leader in the travel and retail analytics space

Jan 2021 – Mar 2021 · 2 mos · Santa Clara County, California, United States

• Developed a system to calculate the Customer Lifetime Value (CLTV) for customers acquired through marketing channels to optimize the bidding mechanism for the channels
• Analyzed the performance of marketing channels based on the survey results and the figures reported by portals of those channels to plan the monthly marketing budgets
• Built a recommendation system to provide feedback on the channels selected for airing on Linear TV based on the historical performance

Sep 2020 – Dec 2020 · 3 mos

• Augmented and automated the sales realization pipeline by understanding the client consumption details and improve the revenue forecasting model by 6%
• Refined quantitative data analysis operations (funnel analysis) to handle clients with critical gaps in data that increased the deals considered in the analysis from $2M to $11M
• Developed intuitive dashboards in Tableau to generate Sales Realization report to help the marketing team target clients (segmentation analysis) and market products that have the highest ROI

Jun 2020 – Dec 2020 · 6 mos · Pittsburgh, Pennsylvania, United States

• Conducted hypothesis testing and presented insightful findings to the PA government and stakeholders from - finance, energy, and health sectors to identify the disproportionately affected businesses and populations in the state
• Developed data-driven decision support tools to aggregate public, private, and state-agency collected datasets to design strategies and policy interventions for safely re-opening the economy
• Automated the generation of reports to study the impact of the lockdown on vulnerable populations and businesses by analyzing 5 million bank accounts from 1.5 million households in Pennsylvania, saving up to 30 developer hours per week
• Developed end-to-end data pipelines (ETL) and dashboards in Tableau to track the metrics such as the ICU Capacity risk, Reopening Contact risk, and others to keep the stakeholders updated of the evolving COVID-19 situation in the state
• Modeled and analyzed travel patterns of people over time using PostgreSQL and Post GIS to identify vulnerable hotspots and changes in the trends in travel patterns during the lockdown to minimize contact

Jun 2017 – Jan 2019 · 1 yr 7 mos · Pune

• Designed ERD, SQL tables, and optimized existing queries to filter and fetch data for a Smart city management platform that reduced turnaround times by 30% from 300ms to 210ms
• Implemented the core functionality for a predictive maintenance solution that reduced resolution times by 40%
• Developed Data Pipelines leveraging reusable patterns resulting in a decrease in the developer estimates by 20%
• Created dashboards to monitor and anticipate the budget utilization rate by employing the current cash-flow rate
• Designed custom lightweight REST APIs for several systems such as asset entry/management, inspections life-cycle management, and work-orders management
• Curated sprint backlogs and executed user stories through UAT as a developer in an Agile environment
• Mentored a team of 3 interns dedicated towards customer success, including bugs triage, analysis, and resolution

Jun 2015 – Jun 2016 · 1 yr · Pune

• Designed​ an application to document the effective working hours of the employees
• Provided selective access to this information based on the employee’s position in the company hierarchy
• Generated visual analytics in the form of weekly and monthly reports
• Tech stack: Java - Android, SQLite, Flask