name: Kshama Upadhyay
role: Finance Analyst — Financial Modeling, Pricing Analysis & Assumption Validation
location: Boston, MA
education:
- MPS, Analytics — Northeastern University (GPA 3.5)
- B.Com, Business, Finance & Economics — Mithibai College, Mumbai
experience: Business & Data Analyst @ FinEdge Analytics (financial analytics firm)
built: Battery storage project finance & capacity pricing model 🔋
superpower: Catching discrepancies before they reach an output- 📊 I build, audit, and troubleshoot Excel financial models — DCF, NPV/IRR, cost of capital, and capital stack construction.
- 🔍 At FinEdge Analytics I reconciled 1M+ rows across 5+ source systems, improving reporting accuracy by 30%.
- ⚡ Automated month-end reconciliation with Excel, VBA & Power Query — 4+ hours → under 15 minutes.
- 📈 Built and maintained 15+ KPI dashboards for senior leadership in Power BI, Tableau, and QuickSight.
- 🗣️ I like turning model output into plain-language summaries that non-finance stakeholders can act on.
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Translating model output for non-finance stakeholders · Concise written summaries · Leadership reporting · Presentations · Cross-functional collaboration · Raising deadline risks early
| Project | What it does | Stack |
|---|---|---|
| 🔋 Battery Storage Project Finance & Capacity Pricing Model | 400 MW storage + backup generation portfolio: capex, O&M, degradation and capacity revenue → monthly cash flows; senior + mezz debt sculpted to target DSCR; NPV, project/equity IRR, sensitivity tables and the capacity price needed to hit a target return, verified against a Python reference model | Excel · Python |
| 📒 FP&A Budget vs. Actual & Rolling Forecast Model | Annual budget for a $48M distributor (21 lines, 5 departments), monthly and YTD budget-to-actual reporting with variance flags, rolling 9+3 forecast, P&L to EBITDA and management commentary, verified against a Python reference model | Excel · Python |
| 🏗️ Five-Year Strategic Plan, Consolidation & CAPEX Model | Four-business building materials group: FRED macro-driven volume × price plans consolidated with intercompany eliminations into the annual budget and five-year plan; CAPEX budget vs. forecast tracking, project NPV/IRR, free cash flow, EBITDA bridge, scenarios and a board deck | Excel · PowerPoint · Python |
| 🏥 Hospital Quality Benchmarking: Massachusetts vs. US | CMS data on 5,419 hospitals loaded into a DuckDB star schema with 15 standardized validation checks; benchmarks 55 Massachusetts hospitals against 3,107 US peers on readmission, mortality and patient safety | SQL · Python · DuckDB |
| 🔀 Healthcare Data Integration Pipeline | Lands six CMS hospital quality files (≈800K rows) in HDFS, loads Hive tables and maps five different source layouts to one standard format with config-driven PySpark; 22 data quality checks with row-level reconciliation, HiveQL marts, Bash and PowerShell runners | PySpark · Spark SQL · Hive · HDFS |
| 📉 Pricing, Cost Variance & Vendor Delivery Analysis | Which categories and vendors drive gross-margin changes, and is that tied to vendor delivery performance? | Snowflake SQL · Python · Power BI (DAX) |
| 🎯 Sales Funnel Analysis & Lead Scoring — Set2Close | Master's capstone: root causes of funnel drop-off and lead scoring, presented to leadership for strategic planning | SQL · Python · Power BI · Tableau |
| ⚙️ Hospital Quality API | REST microservice on CMS data for 5,419 hospitals: trie autocomplete, LRU cache, heap top-k and rate limiter built from scratch; SQL and DynamoDB repositories, retries and circuit breaker, AWS SAM (Lambda, API Gateway, DynamoDB), GitHub Actions CI, 98% test coverage | Python · FastAPI · AWS · DynamoDB |
| 🔮 Customer Churn Prediction Microservice | REST API that scores customer churn risk from behavioral features | Python · FastAPI · scikit-learn |
