A data-driven PM building 0→1 products where analytics meets decisions.
I'm Sneha Santhoshkumar — a technical Product Manager with a computer-engineering foundation and an analyst's instinct. I write SQL daily, ship dashboards teams rely on, and deploy directly alongside customers to turn ambiguous problems into shipped, measurable products across SaaS and fintech.
Forward-Deployed Problem Solver
Impact, role by role.
Where I've shipped — the headline metrics up front, then how I got there.
AI-powered credit automation at scale
- Own daily SQL across Credit, Collections & AR for a platform serving 100K+ users at $1M ARR (17% CAGR), powering the Tableau & Power BI dashboards internal and sales teams use to make decisions.
- Architected an AI-powered OCR pipeline with automated data-quality checks that catch issues before users report them — cutting processing time 30%.
- Ran 67 stakeholder sessions to diagnose failing tools and embedded fixes at the root, reducing turnaround 70%.
- Launched an iPaaS integration platform for Credit & AR in 3 months, designing the data models and validating end-to-end reconciliation.
AI portfolio tools, taken to market
- Executed a 3-phase product roadmap around AI portfolio management, asset tracking, and dividend tools to take the product to market.
- Translated ambiguous stakeholder questions into structured analyses with clear takeaways — improving delivery timelines 10% and cutting defects 60%.
- Tied data directly to revenue outcomes for both technical and business audiences, lifting revenue per user 20%.
Finding the churn signal in the noise
- Built visualizations from raw data to uncover the patterns driving churn, then translated them into actions the team executed — reducing churn 37% and reaching a CSAT of 83%.
- Wrote complete user stories and acceptance criteria meeting the Definition of Ready, accelerating dev handoff and cutting blocker-related delays 30%.
- Delivered interactive dashboards in Tableau & SQL that gave stakeholders real-time project insight.
An analytics layer built from zero
- Architected the analytics layer from scratch for a mental-health platform, tracking behavior and identifying the engagement drivers that shaped the roadmap.
- Scaled the platform to 10K interactions in two months by turning insights into product decisions across a team of 20.
- Owned communicating findings to non-technical stakeholders — the hardest and most valuable skill in the role.
Frame the problem, instrument it, prototype fast, ship & decide.
Frame
Sit with the customer and stakeholders to find where tools quietly fail people.
Instrument
Write the SQL and build the dashboards so decisions rest on data, not opinion.
Prototype fast
Decompose into MVP stories, map the data models, and build to validate quickly.
Ship & decide
Launch, measure the outcome, and embed fixes at the root to prevent recurrence.
Projects across product, data & AI.
A mix of product strategy, data engineering, and ML work — from graduate projects at UIUC & Mumbai to personal builds.
Financial Manager Application
Led development of a fintech financial-management tool on a $100K budget and a 6-month agile schedule. Ran a matrix team across engineering, cybersecurity, and UI/UX, integrated AI-driven insights, and drove a stakeholder communication plan to keep everyone aligned.
Yelp Data Integration & Insights
Engineered a pipeline converting Yelp JSON into a structured MySQL database on Azure, with full documentation and metadata standards. Wrote SQL queries surfacing strategic insights to guide new-business launch decisions; collaborated via Kaggle & Google Colab.
Disrupting Hospitality: Airbnb
Analyzed Airbnb's disruption of hospitality — +30% user satisfaction vs. traditional stays. Forecast trends projecting +20% market share over 5 years and ran user research lifting engagement 25% and repeat bookings 15%.
Target Corp. Financial Analysis
Assessed Target's financial health — cash balance, net receivables, and ratios against industry benchmarks — building dynamic Excel models for investment evaluation. Led a team of five and presented findings recognized for analytical rigor.
Red Robin Marketing Plan
Defined scope and built a go-to-market plan to grow Red Robin's market share and revenue. Analyzed internal/external dynamics and engineered product-marketing strategies — including healthy & vegan lines — to capture emerging segments.
SentinelStream — Fraud Detection
A real-time fraud-detection engine built from zero — designed the data schemas, wrote ingestion & transformation logic in Python/SQL, and validated output quality end to end on a streaming stack.
Enterprise AI Knowledge Search
An AI search system using OpenAI embeddings + Pinecone, with designed evaluation metrics (Precision@K, MRR, NDCG) and an automated workflow to measure search quality at scale.
Breast Cancer Detection
Built a CNN with computer vision to detect breast masses and calcifications and classify benign vs. malignant tumors — 96.84% accuracy on the mammogram dataset, deployed via a Gradio web interface.
Fake Profile Detection
Designed an ML system to detect fake social-media profiles used for propaganda. A Support Vector Machine hit 91% accuracy, outperforming Naïve Bayes and Random Forest baselines.
Global Wheat Detection
Detected wheat heads from field imagery and inferred traits — head health, disease, and population density — using a CNN that reached 98.6% accuracy.
Learning in the room where product happens.
I stay close to the product community — conferences, meetups, and leadership forums where I learn from the people shaping the craft.
ProductCon by Product School
Joined the world's largest product-management conference in New York — sessions on AI-native product, discovery, and go-to-market from leaders across the industry.
Fintech Leadership Forum
Attended the Fintech Leadership Forum hosted at Adyen — connecting with product leaders on payments, credit, and the future of fintech workflows.
ProductTank Leadership Panel
Part of the ProductTank community — panel discussions and talks where PMs trade hard-won lessons on prioritization, metrics, and building the right thing.
Between engineering, data, and business.
I build products at the intersection of data and user need. Right now I own roadmap, discovery, and go-to-market for enterprise B2B SaaS in fintech, where the workflows I help shape directly affect how large organizations manage credit and cash flow.
My background spans fintech, payments, and accounts-receivable automation — domains where getting the workflow wrong costs real money. That context sharpens how I prioritize: I dig into the "why" through customer discovery, behavioral analytics, and close collaboration with engineering, sales, and CS.
On the craft side, I write PRDs engineering teams actually use, run structured discovery and usability sessions, and translate messy feedback into clear roadmap decisions. I'm comfortable going deep in data — queries, dashboards, frameworks — and equally comfortable presenting strategy to VPs or walking customers through betas.
Core Skills
Education
- MS, Technology Management University of Illinois Urbana-Champaign · STEM
- BE, Computer Engineering University of Mumbai
Certification
- Certified Scrum Product Owner (CSPO)
