---
title: "Somay Vaidh - Senior Associate data analyst in Bengaluru | Tal"
description: "Meet Somay Vaidh, Business Analytics & Product Analytics| The Souled Store | Ex-Deutsche Bank, OLA, Snapwork Technologies NUS,DIGII | Skilled in Python, SQL, Machine Learning, Data Visualization based in Bengaluru. AI stack includes claude code, claude, and lovable."
image: "https://tal.club/meet/somay-vaidh/share-image"
---

# Somay Vaidh on Tal

## Headline

Business Analytics & Product Analytics\| The Souled Store \| Ex\-Deutsche Bank, OLA, Snapwork Technologies NUS,DIGII \| Skilled in Python, SQL, Machine Learning, Data Visualization

## About

I’m a Computer Science graduate from Vellore Institute of Technology \(VIT\) with a strong foundation in technology and a deep passion for data science\. Throughout my academic journey and professional internships, I’ve gained hands\-on experience in machine learning algorithms, data analysis, and building real\-world projects that solve meaningful problems\. With certifications in data science and machine learning, I’ve continuously worked on enhancing my technical skill set while applying these concepts to personal and internship\-based projects\. My background combines both practical knowledge and analytical thinking, equipping me to contribute effectively in data\-driven environments\. Currently, I’m actively seeking opportunities as business analyst, data analyst, data engineer so that I can apply my skills to impactful challenges, and collaborate with innovative teams\. Let’s connect and explore how we can work together to unlock the power of data\.

## Location

Bengaluru

## AI stack

claude code

claude

lovable

replit

ChatGPT

Gamma

## Work experience

Senior Associate data analyst at The Souled Store, May 2026 \- Present · 5 mo, Mumbai, Sole analytics partner to Retail Operations for 80\+ COCO & franchise stores: own monthly targets, performance reviews and store diagnostics \(footfall, conversion, AOV, UPT, ASP , sell\-through\)\. Category deep\-dive on perfume across 74K\+ customers \(cohort retention, SKU migration, cannibalisation\); store\-level targeting from it helped lift perfume share of sales from 1\.5% to \~3%\. Automated monthly target phasing into daily, state\-wise store targets \(weekdays, holidays, retail events\), cutting 3–4 days of manual work to a repeatable run\. Built a store anomaly report combining audit, replenishment, returns, perfume and high\-value\-bill signals; tracks 20–25 at\-risk stores and flags 10–12 in red for Retail Ops each cycle\. Updated the monthly Store MIS / P&L and Revenue Dashboard \(Finance\-owned\) for 80\+ stores across 40\+ cities, and analysed store\-wise margins, LFL growth, rent and salary costs to find where costs could be cut and sales grown\. Automated 15\+ reports and alerts \(stock, shrinkage, hourly footfall via API, daily KPI report\) with SQL, Python and BigQuery, saving 20\+ hrs/week and moving reporting from weekly to daily\. Designed a returns\-abuse framework for CXOs: flagged high and cross\-store returners, who were routed to Customer Experience for call\-backs\. Run the fortnightly franchise business review; built a like\-for\-like footfall view that showed one store's conversion drop came from fixture damage \(display use 100%→43%\), not demand\. \.

Business Analyst and Program Manager at SnapWork Technologies, Jun 2025 \- May 2026 · 1 yr, Mumbai, Led analytics and data modeling for the Personal Finance Manager \(PFM\) product by structuring raw bank, credit card, EMI, investment, and income data into clean, analyzable user\-level datasets, enabling accurate monthly savings and cash\-flow insights\. Defined and instrumented end\-to\-end PFM user journeys \(onboarding → account linking → transaction categorization → insights → action\), tracking key product metrics such as activation rate, category accuracy, savings variance, and insight adoption\. Designed event instrumentation and KPIs to identify product blind spots including credit card partial repayments, variable income spikes, infrequent investments, and irregular expenses, directly improving financial insight accuracy and user trust\. Built product and business dashboards across PFM, MedGo consumer app\(Health Insurance\), and MediCard\(Health Insurance\), tracking MAU, funnel drop\-offs, digital vs offline usage, claim settlement TAT, and repeat usage, enabling data\-driven prioritization for product and operations teams\.

Program manager and business analyst at Ola, Nov 2024 \- May 2025 · 7 mos, India, Served as the primary point of contact for launching the Gift Cards category on the Open Network for Digital Commerce \(ONDC\), collaborating with Directors and stakeholders to define data\-backed strategies and executional frameworks Built granular customer cohorting models—including lifetime order bucketing, AOV, frequency, new vs\. repeat, retention, and detailed RFM segmentation—where I identified champions, cold leads, and at\-risk users through a cross\-category RFM matrix\. Applied these insights across Food & Grocery \(category/subcategory frequency and LTO\-based cohorts\) and platform\-wide reactivation analysis, enabling targeted UX and marketing interventions that boosted repeat orders by 20%\. Developed automated dashboards and performance reports, tracking key business KPIs such as conversion rates, inventory turnover, and sales growth, enabling data\-driven business expansion strategies\. Collaborated on data pipeline workflows for real\-time analytics dashboards using Hive, Presto, and internal BI tools\. Performed geospatial analytics using Python \(Geopandas, Folium\) and SQL to identify dark store hotspots for Ola Grocery, optimizing store placement based on order density, delivery feasibility, and market demand insights\. Worked in creating an Internal AI agent “Kya Chal Rha Hai” for CEO’s office which summarizes all the weekly updates for the organization in phases of blockers,progress,etc\. Built using Gmail API and Ollama\.

Business Program Manager at Ola, Nov 2024 \- Apr 2025 · 6 mos, ●​ Served as the primary point of contact for launching the Gift Cards category on the Open Network for Digital Commerce \(ONDC\), collaborating with Directors and stakeholders to define data\-backed strategies and executional frameworks\. ●​ Built granular customer cohorting models—including lifetime order bucketing, AOV, frequency, new vs\. repeat, retention, and detailed RFM segmentation—where I identified champions, cold leads, and at\-risk users through a cross\-category RFM matrix\. Applied these insights across Food & Grocery \(category/subcategory frequency and LTO\-based cohorts\) and platform\-wide reactivation analysis, enabling targeted UX and marketing interventions that boosted repeat orders by 20%\. ●​ Developed automated dashboards and performance reports, tracking key business KPIs such as conversion rates, inventory turnover, and sales growth, enabling data\-driven business expansion strategies\. ●​ Collaborated on data pipeline workflows for real\-time analytics dashboards using Hive, Presto, and internal BI tools\. ●​ Performed geospatial analytics using Python \(Geopandas, Folium\) and SQL to identify dark store hotspots for Ola Grocery, optimizing store placement based on order density, delivery feasibility, and market demand insights\. ●​ Worked in creating an Internal AI agent “Kya Chal Rha Hai” for CEO’s office which summarizes all the weekly updates for the organization in phases of blockers, progress, etc\. Built using Gmail API and Ollama\.

Data Analyst Intern at Deutsche Bank, Jul 2024 \- Sep 2024 · 3 mos, Pune, Maharashtra, India, Analyzed multi\-million row financial datasets to detect credit risk anomalies and trade execution discrepancies\. Leveraged SQL and Python \(Pandas, NumPy\) to analyze large financial datasets, detecting patterns in credit risk, liquidity shifts, and market volatility\. Identified anomalies in transaction data \(outlier risk events & trade discrepancies\), supporting strategic risk mitigation and improving portfolio management decisions\. Built predictive models \(Scikit\-learn, Statsmodels\) to assess market risks, reducing manual analysis time and improving forecast accuracy\.

Product Analyst at Digii \(formerly CollPoll\), Jan 2024 \- Jun 2024 · 6 mos, Bengaluru, Karnataka, India, Interacted with clients on a daily basis and help them in onboarding of the software\. Issued client's queries and giving a turnaround solution\. Worked on client's data with the help of advanced Microsoft excel and Python \. fixed bugs and helped in creating a new feature for the software

Product Specialist at Digii \(formerly CollPoll\), Jan 2024 \- Jun 2024 · 6 mos, ●​ Interfacing with clients to facilitate software onboarding and ensuring seamless integration with existing university systems\. ●​ Analyzed real\-time client data, including university and student datasets, using Microsoft Excel and Python \(Pandas, NumPy\) to extract actionable insights, support data\-driven decision\-making, and optimize product features\. ●​ Worked on the examination module, leveraging data analysis to automate question paper generation, ensuring compatibility with client systems and improving overall efficiency in the product workflow\.

## Education

Bachelor of Technology \- BTech, Computer Engineering, Vellore Institute of Technology

Rajhans Vidyalaya

[View the original profile](https://tal.club/meet/somay-vaidh)

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