Akshat Mehta

Business Development Executive

Jalandhar, Punjab, India1 yr 10 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Led multiple A/B experiments to improve ad performance.
Developed key metrics to enhance seller ROI.
Strong background in data analysis and product management.

Stackforce AI infers this person is a data-driven product analyst in the SaaS industry.

Contact

Skills

Core Skills

A/b TestingHypothesis TestingSqlData AnalysisProduct Management

Other Skills

Microsoft ExcelCollaborationRoot Cause AnalysisDashboard DevelopmentBusiness StrategyProblem SolvingStatisticsComputer VisionOpenCVConvolutional Neural Networks (CNN)Real-time SimulationEmbedded JavaScript (EJS)Computer Science EducationTeam-focusedCascading Style Sheets (CSS)

About

I’m a data professional with 2+ years of experience at Meesho, working on the demand side of the Ads team. My work focuses on using data to understand advertiser behavior and improve product outcomes. In my role, I work closely with product and business teams to analyze data, define metrics, and run A/B experiments. I’ve owned experiments end to end—from setting up hypotheses and tracking performance to analyzing results using statistical methods. I enjoy solving product problems through data and experimentation, and I’m interested in moving into product/product analytics roles where I can contribute to building and improving products.

Experience

1 yr 10 mos

Total Experience

1 yr 10 mos

Average Tenure

1 yr 10 mos

Current Experience

Meesho

2 roles

Buisness Analyst II

Jan 2026 – Present · 4 mos · Bengaluru · On-site

• Fully owned and led multiple A/B experiments on the Ads Panel to reduce SLROI and improve seller understanding of the metric. Managed the experiments end-to-end, from hypothesis creation and setup to tracking and analyzing results using statistical methods.

A/B TestingHypothesis Testing

Buisness Analyst

Jun 2024 – Dec 2025 · 1 yr 6 mos · Bengaluru · On-site

Led the scale-up of the new Ads product ROI Plus as part of the Feedback Pod, collaborating with a 3-member team to improve the ads feedback loop, driving a 10% increase in campaign revenue by improving key seller ROI metrics.
Built and owned the core Presto model that generates campaign feedback, increasing actionable feedback coverage from 10% to 25% through root cause analysis and improvements to product logic.
Increased seller feedback adoption from 18% to 23% by identifying funnel drop-offs, conducting exploratory data analysis, and working with sellers to address issues around comprehension and margins.
Automated the sale budget deployment process and performed RCA during sale events, reducing failure cases from 12% to 5% on average.
Developed the company’s Overall ROI metric to measure incremental orders driven by ads, and built a Superset dashboard enabling product and data science teams to track the impact of improvements to the ads system.

SQLMicrosoft ExcelData Analysis