Toronto, Canada | UTSC Statistics Co-op

MD Awsaf Hossain

Aspiring Quant Finance Analyst | Markets + Statistics + Programming

I build data-driven finance projects across backtesting, modeling, and analytics to prepare for quant research, trading, and finance internships.

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About Me

I am a University of Toronto Scarborough Statistics Co-op student in the Quantitative Finance stream, with a BBA background in Management Finance. My path combines business and technical training: programming experience in Python and C, practical finance exposure through internships at Heineken Canada and Teesta Solar, and continuous project-based learning across data, markets, and modeling. I am intentionally building toward quant finance by strengthening mathematical foundations, developing coding depth, and applying finance concepts through hands-on analysis and strategy work.

Education

University of Toronto Scarborough

Honours Bachelor of Science, Statistics Co-op – Quantitative Finance Stream

Relevant coursework: Calculus I/II, Linear Algebra I/II, Differential Equations, Discrete Mathematics, Data Structures, Python Programming, C Programming, Microeconomics, Macroeconomics, Financial Accounting, Management Accounting, Probability, and Finance/Investments.

Academic progression reflects strong technical growth, including an A+ in CSCA08 and a strong Calculus I performance as key milestones in my comeback journey.

Skills

Quant Research

Backtesting, market data analysis, strategy evaluation, regime testing

Programming

Python, C, SQL, VBA, file parsing, data structures

Mathematics

Calculus, Linear Algebra, Differential Equations, Probability, Discrete Math

Financial Analysis

DCF valuation, financial modeling, forecasting, budgeting, sensitivity analysis

Data Stack

Excel, Power BI, Alteryx, data cleaning, dashboards, automation

Experience

Finance Intern – Heineken Canada

Built Power BI dashboards across sales and finance datasets; supported time-series trend analysis, forecasting, pricing and discount analysis, and Python-based automation for recurring reporting workflows.

Junior Financial Analyst – Teesta Solar Ltd.

Developed a 20-year revenue model and DCF valuation model with sensitivity analysis for solar project finance decisions; helped define KPI dashboards for performance tracking.

Finance & Marketing Director – Data Science and Statistics Society, UofT

Managed Datathon budgeting, sponsor coordination, financial documentation, and KPI tracking to support financially sustainable and well-executed student events.

Co-Founder – ChattoTurf Sports Arena

Led financial planning and cash-flow modeling, supported operations across four venues, and coordinated teams to keep execution aligned with growth goals.

Featured Projects

Implied Volatility Surfaces and the Variance Risk Premium

Building implied volatility surfaces from OptionMetrics index option data and comparing the variance risk premium across US and Canadian equity exposure. Black-Scholes priced on the forward, implied volatility recovered by Brent inversion, SVI surface fits tested for butterfly and calendar arbitrage violations.

Status: In progress. Pricer and analytic vega complete, validated against put-call parity, monotonicity in volatility, payoff convergence at expiry, and a finite-difference check.

Design note: UofT's WRDS subscription has no Canadian IvyDB coverage, so the Canadian leg uses NYSE-listed EWC options. This measures how US investors price Canadian equity risk, currency-unhedged, which is documented as a limitation.

PythonSciPySQLWRDS / OptionMetricsOptions Pricing

Quant Trading Strategy Backtest

Python backtesting framework using TSLA market data with transaction costs, signal rules, volatility targeting, and market regime testing.

Result: Strategy edge weakened out-of-sample after realistic cost controls.

PythonBacktestingMarket Data
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Ingredient Networks Graph Project in C

Built a graph-based ingredient network using an adjacency matrix, recursive k-hop search, and exclusion filtering with scalability to 400 ingredients.

Method: Recursive graph traversal and matrix-based relationship scoring.

CGraphsRecursion
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Music Data Structures Project in C

Implemented binary search trees and linked structures with recursion, file parsing, traversal, deletion, reversal, and harmonization logic.

Thesis: Efficient structure design improves correctness and speed in low-level C workflows.

CData StructuresBST
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Movie Review Database Project in C

Designed a pointer-based linked-list database supporting insert/search/update/sort/delete operations and profitability analysis.

Method: Pointer-safe linked-list operations with modular query and ranking logic.

CLinked ListsDatabase Logic
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Ontario Bridges Data Analysis Project in Python

Processed CSV infrastructure data to analyze bridge conditions, perform distance-based filtering, and build priority ranking logic for inspection planning.

Result: Produced a reproducible prioritization workflow for inspection decision support.

PythonData AnalysisCSV Processing
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Currently Building Toward Quant Finance

  1. Advance Python workflows for cleaner research and faster analysis cycles
  2. Deepen probability, statistics, and stochastic reasoning for market uncertainty
  3. Expand backtesting research with stronger risk controls and regime awareness
  4. Use C and data structures to strengthen algorithmic and systems thinking
  5. Apply financial modeling and valuation in practical investment scenarios
  6. Next focus: options pricing, portfolio optimization, and ML for market signals

Resume & Contact