CV templates for finance and technology

First-class trajectory: 78% first-year average. Modules: Corporate Finance, Econometrics, Financial Accounting.

Head of the school investment club; grew a 20-member paper portfolio 14% in one year.

• •Built a three-statement model and DCF valuation for a £45m consumer transaction, testing WACC and exit multiples across 6 scenarios
• •Analysed 30 comparable transactions to benchmark EV/EBITDA multiples, feeding the pitchbook presented to the client board
• •Presented a 10-page sector screen on UK fintech M&A to 2 directors, shortlisting 8 acquisition targets for outreach

• •Led a 4-person team to 2nd place of 40 in a valuation challenge, defending an LBO thesis to practitioner judges
• •Drafted weekly M&A briefs read by 350+ members, growing the open rate from 31% to 48% in 3 months

• •Handled 200+ transactions per peak shift while studying for A-levels
• •Trained 3 new team members on till and service standards, cutting average order time by 15%

CFA Level I passed (Aug 2025). Coursework: Equity Analysis, Financial Statement Analysis, Econometrics.

• •Built earnings models for 8 software companies under coverage from 10-K and 10-Q filings, updating estimates within 24 hours of each print
• •Drafted 3 sections of an initiation report on vertical software, including the competitive landscape and a 40-company comps table
• •Summarised 25 earnings calls into one-page notes used by the senior analyst in client conversations

• •Covered 6 technology holdings in a $1.2M student-run portfolio, presenting quarterly updates to the investment committee

• •Recommended a long at $42 with a $58 target from a 3-stage DCF and transaction volume analysis; the fund took a 4% position

Michigan Investment Banking Club; Ross Dean’s List (6 semesters).

• •Built the LBO and sponsor returns analysis for the $850M take-private of a healthcare services company (closed), testing 5 leverage cases
• •Modelled the carve-out of a $300M diagnostics division, including the standalone cost base and transition services agreement
• •Identified $40M of overstated synergies in a buyer’s case, which reduced the bid and was adopted in the final offer letter
• •Ran the buyer process for a $150M sell-side mandate across 45 parties, managing the data room and 12 management meetings

• •Prepared comparable company and precedent transaction analyses for 4 pitches, 1 of which converted to a mandate

Thesis: calibration of rough volatility models under limited option data. Supervised by a professor of mathematical finance.

Part III: Stochastic Calculus, Advanced Probability, Optimal Transport.

• –Built a gradient-boosted signal on order-book features for 40 futures contracts, adding 0.3 to out-of-sample Sharpe after costs over 2 years
• –Reduced backtest run time from 6 hours to 25 minutes by vectorising the feature pipeline in NumPy

• –Taught weekly problem classes for 60 second-year students; rated 4.8/5 in feedback

• –Derived a fast approximation for rough Heston pricing, cutting calibration time 30-fold with under 1 bp of error

• –Wrote a matching engine handling 2 million messages a second, used by 3 students for thesis experiments

• •Called a downgrade of a UK retailer to Sell at 310p on inventory build in channel checks; the stock fell 28% over the following quarter
• •Initiated on 6 European apparel names with a contrarian Buy on a discount retailer at €18; up 41% in 12 months
• •Built a weekly web-traffic and pricing tracker across 14 consumer names, flagging 2 earnings misses a week before results
• •Owned a wrong call on a 2024 beverage upgrade (underweighted input costs); now model commodity hedges explicitly for every name

• •Maintained earnings models for 18 companies and drafted 60+ notes, including 2 sector initiations

Coursework: Operating Systems, Distributed Computing, Machine Learning, Algorithms.

• •Built a rate-limiting service in Go handling 12K requests a second, cutting abuse-related outages from 3 a month to none
• •Added structured logging and tracing across 9 services, reducing median incident diagnosis time from 45 to 12 minutes
• •Wrote 140 integration tests for the payouts API, raising coverage from 52% to 81%

• •Parallelised a Python simulation with Ray across 64 cores, cutting experiment time from 9 hours to 20 minutes

• •Built an open-source study planner with 4,000 monthly users and 1,200 GitHub stars; 14 outside contributors

• •Implemented leader election and log replication, passing linearisability tests under simulated network partitions

• ▪Shipped a retrieval system over 400K support articles serving 30K queries a day, raising answer accuracy from 71% to 88% on a 1,200-question test set
• ▪Cut inference cost 46% by routing 70% of traffic to a smaller fine-tuned model, with no loss on the evaluation suite
• ▪Built the regression suite that every prompt and model change must pass, blocking 9 quality regressions before release

• ▪Deployed a document classification service handling 5M documents a month at p95 latency under 120ms

• ▪Wrote a small library for pairwise model evaluation with confidence intervals; 2,300 GitHub stars

• •Shipped a churn model (gradient boosting, 0.81 AUC) driving a retention offer that reduced monthly churn from 4.1% to 3.4% in an A/B test
• •Designed and analysed 22 pricing experiments, introducing CUPED to cut required sample sizes by 35%
• •Built the feature pipeline in dbt and Airflow serving 6 production models, with drift alerts reviewed weekly
• •Replaced 14 manual reports with one self-serve Looker model, saving the finance team 2 days a month

• •Published a reproducible benchmark on 2M anonymised transactions, cited in 2 conference talks

• •Led a 7-person client team to launch a mobile onboarding flow, raising completed applications from 38% to 61% in 3 months
• •Ran 24 user interviews that cut a planned 9-feature release to 3, delivered 6 weeks early
• •Wrote and prioritised the backlog for a 12-engineer team across 8 two-week sprints

• •Built the business case for a £30m claims platform rebuild, approved by the client board
• •Analysed 2M claims to find 4 process bottlenecks, cutting average claim time from 11 to 7 days

• •Led the quality-of-earnings workstream on the £120m sale of a logistics group, adjusting EBITDA by £3.4m and informing the final price
• •Drafted the financial due diligence report for 6 buy-side mandates, presenting key findings to private equity clients alongside the partner
• •Built the net debt and working capital analysis for a £400m carve-out, identifying a £9m normalisation adjustment adopted in the SPA
• •Supervised 3 associates across 2 concurrent deals, reviewing every schedule before it reached the client

• •Audited 9 mid-market clients in industrials and consumer, with revenues from £30m to £250m
• •Seconded for 6 months to transaction services, working on 3 vendor due diligence reports

First-time passes in all 15 papers.

Modules: Probability, Stochastic Processes, Financial Economics. 72% second-year average.

• •Built a pre-market briefing on G10 rates for the desk each morning, read by 8 traders for 6 weeks
• •Wrote a Python tool to reconcile 300 daily swap trades against the booking system, cutting the check from 40 minutes to 5
• •Pitched a curve steepener idea to the head of desk on the final day, sizing it with a simple DV01 calculation

• •Ran a weekly markets briefing for 180 members and organised a trading game with 64 entrants