Jack Hughes

I'm Jack Hughes

I'm a

I build things that work, and I can sit in the room and explain them. Products, tools, and systems from idea to production, deployed alongside the people who use them.

GitHubResume

01. about

Who I Am

I'm Jack, a builder who sits at the intersection of product thinking, technical execution, and the conversation that connects the two. I'm most at home when I'm embedded with a customer: scoping the real problem, picking the right stack, and getting something live in front of them.

My background spans both the business side and the code side, with a FinTech concentration at Northeastern and now a Master's in Data Science at Boston University. I've built automation pipelines, BI reporting, web products, and more. The kind of stuff where you own the whole thing, not just one layer. I care less about titles and more about whether the thing works and the person across the table trusts it.

Outside of building things, I'm drawn to how technology actually changes how people work, not the hype but the real shifts. I'm also a steak-cooking aficionado, a corporate basketball league champ, and someone who reads too much about things he doesn't need to know.

jack@portfolio ~ %
// currently building
const focus = "data, automation & AI products";
// based in
const location = "New York, NY";
// education
const education = [
"MS Data Science · Boston University",
"BS FinTech · Northeastern"
];
// open to
const openTo = [
"interesting problems",
"collaborations",
"good conversations"
];
// github
github.com/jhughesbu
60+
Demos Delivered
2,000+
Stakeholders Engaged
All Levels
ICs to C-Suite

02. experience

Worked With

teams and clients I've shipped alongside

S&P Global
Financial Data & Analytics
AMC Networks
Media
John Hancock
Financial Services
Octus
Private Credit Intelligence
Alvarez & Marsal
Consulting
Blockchain Founders Fund
Venture Capital

03. corporate projects

Corporate Projects

client and employer work, under NDA but here's the gist

DocuSearch

1st Place · i3 AI Hackathon

S&P Global · Automation Manager

Led a team of developers and subject-matter experts to take 1st place at the i3 AI Hackathon, selected over 400 teams and 1,000+ participants by a panel of C-suite judges. The winning product: a full-stack LLM-driven document search tool, originally a Flask web app on the internal Spark API with bulk DOCX ingest, similarity scoring, WebSocket progress, and parallel processing. Later re-architected as a custom RAG pipeline on Databricks that ingests, parses, and semantically indexes 1,000+ equity and multi-asset methodology documents, enabling natural-language search, variant detection, and automated editing at scale.

FlaskPythonSpark APIDatabricksRAGWebSockets
passage: "index rebalance methodology"
SCANNING DOCUMENTS1,247 indexed
Methodology_2024_Q3.docx
94%
Index_Rules_v12.docx
71%
Equity_ETF_Spec.docx
58%
Multi_Asset_Brief.docx
42%
Top Match
Methodology_2024_Q3.docx94%

Atlas

Confidential

S&P Global · Automation Manager

Led the build of a full-stack application that centralizes ETF launch and workflow tracking across the org. Replaced fragmented trackers and email threads with a single source of truth, saving ~20 hours a week across 200+ global stakeholders and giving leadership real-time visibility into every launch in flight.

Power AppsPower AutomatePower BISharePointDatabricksJiraREST APIs
ATLAS · 14 ETFs IN FLIGHT20 hrs/wk saved
PLANBUILDREVIEWLAUNCH
S&P 500 ESG Index
LAUNCHED
DJ Emerging Markets Bond
IN REVIEW
S&P Tech Pure-Play
BUILDING
DJ Sustainable Real Est.
PLANNING
200+ stakeholderssingle source of truth

P/E Valuation Pipelines & Dashboards

Confidential

Alvarez & Marsal · Forward Deployed Engineer, Private Equity

Launched a Power BI dashboard and end-to-end ETL system serving private equity clients including General Atlantic, Silver Lake, and Patient Square Capital, credited with ~$1M in revenue impact by deepening data analytics for equity client services. Built and maintained the pipelines in Python and SQL with dbt, AWS (EC2, Lambda, S3), and Airflow orchestration, landing the data in Snowflake for Power BI to sit on top.

PythonSQLdbtAWSAirflowSnowflakePower BI
Q3 2024 · PORTCO VALUATIONSrefreshed nightly
GA-01
SL-02
PS-03
GA-04
SL-05
PS-06
$2.4B
AUM
47
PortCos
+$1M
Impact
sourcedbtsnowflakepower bi

Valuation Collection Automation

Confidential

Alvarez & Marsal · Forward Deployed Engineer, Private Equity

Replaced the manual valuation-request workflow (thousands of emails and Excel attachments each quarter) with an automated intake system. Power Apps forms collect responses from PE firms, Power Automate routes follow-ups by portfolio company and file urgency/type, and every submission lands in Snowflake. Cut quarterly completion time by ~60 hours.

PythonPower AutomatePower AppsSnowflakeM365

Sales Intelligence Dashboards

Confidential

Octus (formerly Reorg) · Business Intelligence Developer

Built dynamic Power BI sales dashboards that supported the achievement of a $118M business target, with optimized SQL queries running against 100M+ data points in Snowflake. Also designed and ran A/B testing on Reorg's new bankruptcy algorithm features and UX, with feedback that drove higher client adoption of the product.

Power BISQLSnowflakeA/B Testing

04. projects

Things I've Built

pulled live from github.com/jhughesbu

05. skills

Tech I Work With

the tools, languages, and platforms I reach for

Languages

Python
SQL
Java
VBAVBA

Frameworks

Next.js
React
JSNode.js
expExpress
FastAPI
Tailwind CSS

Data & ML

NumPy
Pandas
Scikit-learn
PyTorch
Jupyter
Airflow
dbtdbt
Databricks

Tools

Vapi.ai
Airtable
Git
OpenAI
Power Automate
Power BI
Power Apps

Cloud & Infra

awsAWS
Azure
BigQuery
Vercel
Railway
GitHub

Video & VFX

PrPremiere Pro
AeAfter Effects

06. contact

Let's Build Something

Whether it's a project idea, a collaboration, or just a good conversation, I'm reachable. No pitch decks required.

© 2026 Jack Hughes

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