Apr 2023 – May 2023 · 1 mo

Jan 2023 – Apr 2023 · 3 mos

Jul 2022 – Feb 2023 · 7 mos

Sep 2021 – Jul 2022 · 10 mos

• Migrated all reports, dashboards, and scripts from SQL to BigQuery at a critical stage of companywide SQL deprecation
• Developed in-house technical solution such as automating survey pipelines, leveraging G-sheet to python integration and more for technical solutions for co-workers and broader team
• Delivered monthly reports and forecast with constantly changing priorities and challenging datasets while optimizing models every month based on business decisions
• Scheduled automated daily audits for troubleshooting and identifying current issues and appropriately flagged to partner engineering teams

Jul 2021 – Sep 2021 · 2 mos

• On the People Analytics Research team our work was majorly divided in to four types of projects.
• Business Research (Analytics) - Project which involved giving direct recommendation to the business based on the insights found. A good example would be Calibration Analysis where our goal was to understand how different pockets of business do their performance calibrations and what works so that we can provide a unified method to the entire company.
• Building Analytical Solutions (Automation) - Our team focused on automating existing analysis in a way that is scaled and replicable with minimal efforts. This is also one of the most important aspect we lean on while doing all our projects. We build solutions by python. Example would be - made a script to fix pay inequity for gender and under represented by looping regression and using binary search algorithm to find an optimal solution which will make sure there is pay equity going forward.
• Methodology research (Innovation) - These are the project where we research into new methods and understand if we can use them for our existing questions to be answered. Eg. Research on survival analysis or may personal fav was implementation of an automated insights generating email. It compared data period over period and generated a summary and insights paragraph which is attached to an email body and sent automatically when you run the scripts.
• External Research partners (Collaboration) - Our team partnered with external researchers from universities like BU and MIT and supported their research work. These project covered understanding various aspects of an employee and employee lifecycle including but not limited to pay, performance, engagement, hiring and exits with the diversity lens

Jan 2021 – Jun 2021 · 5 mos

• PROJECTS
• Performance distribution model: Created a semi-automated distribution range model for the Performance strategy team that will save them 20+ hrs of work every cycle; this model helps performance team make decisions about the upcoming performance cycle.
• Volatility Analysis: Analyzed employee data to understand what’s the impact of manager change and leader change on an employee's performance and engagement; with different business and diversity cuts.
• Management Dashboards: These dashboards in Visier give leaders a view into how their reports are doing from a leadership, career development, and culture perspective and give managers a view into their own management metrics over time. Using these dashboards, leaders and managers can look at their own performance and trends & use them to make new strategies
• Post-Performance cycle analysis: Automated 10+ hrs. of work every cycle for the Performance Strategy team. Build a python script that generates 7 excel files within 3 mins generating all tables and graphs. These reports answer statistical questions about the performance cycle by Workgroups. It has a level cut, and it compares how individual workgroups are doing compared to the target distribution ranges and more post cycle questions
• Corporate L&D Attendance :Collaborated with BI team and Learning and development team to help build Wayfair’s first ever Corporate L&D Attendance dashboard that would report directly from Eden(GBQ). Build BigQuery scripts codebase for the learning teams to self-report from Eden
• What do we know project: The business responds very well to pushed dashboards and information. However, we typically look at this by dataset and let the stakeholders combine insights across datasets, rather than looking by topics and doing that combination for them.
• In this project we went through previous analyses to better understand historical performance and trends to consolidate information topic wise.

Jan 2020 – Aug 2020 · 7 mos · Boston

• Owned the collection, analysis, and reporting of Wayfair’s first candidate diversity dashboard.
• Leveraged SQL, Python, and Google Data Studio to query, restructure, and dashboard data on candidate diversity
• Performed topic modeling on interview feedback text to identify evidence of bias in the hiring process
• Conducted over 20 ad hoc analyses within 6 months on employee diversity data and shared insights with stakeholders at all levels
• Looked at every stage of employee life cycle to record and measure equity using statistical testing

Apr 2018 – Aug 2018 · 4 mos · Mumbai Area, India