sandhya User

I believe data should tell the truth simply — no noise, no spin, just the signal that lets people make better decisions. That's what pulled me into analytics: the craft of turning a mess of numbers into a story someone can act on in five seconds.

I'm a Data Analyst who works across Python, SQL, and Power BI — not because tools are exciting, but because they're the difference between "I think" and "I know." I care obsessively about getting the small things right: a query that runs fast, a dashboard that doesn't need an explanation, a model that actually predicts something useful.

A few things I've built, the way I'd want a hiring manager to read them:

• Optimized SQL queries and indexing at Vorkmint Staffing, improving query performance by 50% — as measured by execution time — by rethinking how the data was actually being accessed instead of just tuning around the problem.

• Cut manual data-validation effort by 30% by automating checks that used to eat analyst hours, freeing the team to focus on judgment calls instead of busywork.

• Built a Healthcare Readmission Risk model on 68,630 patient records across 130 US hospitals, reaching 0.64 AUC with Random Forest, and used it to flag 6,126 high-risk patients — turning a research dataset into something a hospital could actually triage against.

• Built a Telecom Churn model on 7,043 customer records, hitting 78% accuracy, and quantified $139K+ in monthly revenue at risk — then shipped it live on Netlify so it wasn't just a notebook, it was a product.

• Built an HR Attrition model on IBM's 1,470-employee dataset (0.771 AUC) and found that overtime employees churn 3x more often — a simple insight, but the kind that changes a policy, not just a slide.

I'm looking for opportunities where I can apply analytical thinking, build scalable reporting solutions, and help teams make faster, data-driven decisions. If you're hiring, I'd love to connect.