Mihir Khara — Citi, Fordham, Purdue and NMIMS, with a skyline and pillars in data, machine learning, finance and strategy
Photo of Mihir Khara

Statistics · Finance · Always learning

Hi, I'm Mihir Khara

Forever curious, always building.

I write about statistics, finance, and everything I pick up along the way, then turn that curiosity into projects worth sharing. Grounded in a strong academic foundation and real experience at top firms, right where technology meets business.

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Education

Fordham University

Master of Science in Finance (STEM)

Dean's Merit Scholarship | GPA: 4.00 / 4.00

Fordham University, Gabelli School of Business

New York, NYAug 2025 – Dec 2026
Purdue University

Master of Science, Business Analytics and Information Management (BAIM)

Purdue University, Daniels School of Business

West Lafayette, INOct 2021 – Mar 2022
NMIMS

Master of Business Administration in Decision Sciences and Analytics

Narsee Monjee Institute of Management Sciences, School of Business Management

Mumbai, IndiaJun 2020 – Sep 2021

Skills

Stack, domain focus, and credentials in one place.

Languages & Tools

PythonSQLSASTableauPower BIExcel

Machine Learning & Data

Machine LearningDeep LearningStatistical ModelingFinancial ModelingBig DataNLPTime Series Forecasting

Domain

Credit RiskPortfolio ManagementRisk AnalyticsAcquisitionsCustomer ManagementForecasting & Demand PlanningInvestment AnalysisQuantitative ResearchMarketing Analytics

Certifications

Financial Accounting

Harvard Online

Quantitative Methods

Harvard Online

Spreadsheet Modelling

Harvard Online

Experience

Credit risk, portfolio analytics, and data-driven strategy

Three Years in Consumer Credit Risk

Mar 2022 – Jul 2025 · 3 yrs

Citi · Mumbai, India

A quick summary of my time at Citi. Over three years I grew from intern to Analyst II on the consumer credit risk team, owning loss forecasting, acquisition strategy, and the economics of major partnership card portfolios.

SASSQLExcelTableauLoss Forecasting

Technical

  • Led five year Net Credit Loss forecasting and built the Excel and Tableau reporting that fed Citi's annual planning cycle.
  • Automated recurring portfolio reporting with SQL and SAS pipelines, standardizing the metrics used across reviews.

Business & Strategy

  • Shaped acquisition strategy that lifted annual acquisitions by about 20% while holding loss and return targets.
  • Supported the 10 year renewal of a roughly $18bn partnership card portfolio, working through P&L, cost sharing, and profit sharing economics.

Projects & Writing

Financial modeling, credit risk, data engineering, and the blog

Projects

Summer 2026
Financial Modeling & Product

Brass Ring Ventures Capacity Planner

A live web app built during my summer internship at a New York venture firm, modeling delivery capacity and revenue so the team can see when it runs out of headroom and when to hire.

  • Built a supply and demand model that pinpoints the operating partner who runs out of billable hours first, and how many more clients the studio can take on before that.
  • Shipped an interactive dashboard with a live utilization gauge, editable roster and engagements, and what if scenarios, backed by shared Firebase state that syncs across the team in real time.
JavaScriptFirebase FirestoreFinancial ModelingCapacity Modeling
Visit the live app
2026
Credit Risk & Modeling

Credit Risk Analytics Dashboard

My attempt at rebuilding a Power BI credit risk report as a single, self contained HTML page.

  • Tried replicating a Power BI dashboard in plain HTML, CSS, and JavaScript, with every chart hand drawn as inline SVG and no libraries.
  • Reads 307,217 Home Credit loan applications to show who defaults, where the weakest bureau score band defaults nine times more than the strongest.
HTMLCSSJavaScriptInline SVG
Visit the dashboard
2022
Credit Risk & Modeling

Credit Default Prediction in SAS Enterprise Miner

Classification models for credit default using payments, statements, status, and transaction records.

  • AUC of 0.85 after comprehensive EDA and feature tuning.
  • Top 10% in a Kaggle competition; 2nd in the Purdue 2021 cohort.
SAS Enterprise MinerClassificationEDA
2024
Data Engineering & Research

Financial Data Engineering (WRDS, CRSP, Compustat)

A production ready pipeline that merges market returns with company fundamentals into a research grade dataset.

  • Merges CRSP returns with Compustat fundamentals using point in time joins to avoid look ahead bias.
  • Validated for empirical analysis, backtesting, and quantitative research.
WRDSCRSPCompustatPoint in Time Joins
Download the notebook

New York, NY

+1 (551) 384-3496
mihirkhara64@gmail.com