OLU OGIDAN
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Resume / 01

Olu Ogidan

"We should probably do something with AI" is where a lot of teams get stuck. That's the conversation I show up for — figuring out the workflow actually worth touching, building the system, and staying through the part where people start using it. Eight years across Big 4 consulting, the U.S. Senate, and independent client work, mostly in messy environments where the stakes are real.

Last updated
May 2026
Based in
Washington, DC
Email
olu.ogidan@outlook.com
Profiles

Experience / 02

Five roles, one through-line.

  1. U.S. Senate

    Legislative Assistant & AI Operations Lead

    • Lead housing, economic development, tax, and technology policy portfolio — research, stakeholder engagement, briefing memos, and bill drafting for a Colorado senator.
    • Designed and shipped an AI-assisted workflow now processing 3,000+ constituent letters per week and cutting approval turnaround by 90%+. Owned architecture, deployment, staff training, and ongoing fixes end-to-end in a high-ambiguity environment.
    • Built and deployed LegiKit, an AI workflow tool used by 30+ congressional staff across House and Senate offices. Led discovery, definition, development, deployment, onboarding, and adoption — while working full-time on the Hill.
    • Drafted housing policy on property insurance costs, starter-home construction, and eviction prevention. Developed visualizations and executive-ready narratives for Senate hearings, floor speeches, and press moments.
  2. Anchor Data Studio

    Founder & Principal

    • Lead data and AI implementation engagements for mission-driven clients — scoping use cases, defining where human review is required, and building the systems that ship.
    • For Strategic Capacity Group (international capacity-building org), turned a static spreadsheet into a queryable, distributable stakeholder-intelligence database used to target partners by location, availability, and engagement signals.
    • Built a second SCG pipeline ingesting multi-country survey data, structuring unstructured inputs, and producing executive and external-reporting dashboards — outputs that supported a successful $25M grant.
    • For a cybersecurity client, streamlined data-management workflows using Power BI, Power Automate, Excel, and SQL inside their existing tooling.
  3. PwC LLP

    Senior Consultant, Deals Technology

    • Led an analyst team coordinating globally distributed legal, IT, accounting, and M&A teams on data definitions and documentation standards for a multi-million-dollar deal close.
    • Built Excel/SQL journal-entry automation that cut data processing time 80%+; ran cohort, retention, and churn analyses tied to valuation work using SQL, Python, and Power BI.
  4. KPMG LLP

    Associate / Senior Associate, Tax Data & Analytics

    • Built agentic automation that reviewed tax models for errors and warnings — the work became a new client service generating $500K+ in first-year revenue.
    • Generated $300K+ in new business with a dynamic Excel model for clients navigating the Tax Cuts and Jobs Act; raised team efficiency 80% and cut turnaround 50%.
    • Won KPMG's Chairman's Award for client impact and leading community service initiatives across 250+ employees.

Products / 03

Things I've shipped.

  1. LegiKit

    30+ users

    AI workflow product for congressional offices: briefing memos, vote recommendations, and constituent responses, grounded in live bill data and office context. Production stack with WorkOS auth, role-based access, audit logging, rate limiting, and a Markdown → DOCX/PDF export pipeline. React, FastAPI, Postgres, LLM APIs.

  2. Kudoyo

    ~50 active users

    AI career-memory platform for knowledge workers — captures wins, feedback, and milestones, then turns them into grounded reviews, resume bullets, and interview stories. Hybrid retrieval with pgvector + keyword fallback. FastAPI, React, Postgres, Stripe.

  3. Project Sprout

    In beta

    Trust-first debt-planning app with a five-phase tier model. Known / rough / later inputs, visible math, no black-box optimization.

Fellowships / 04

Fellowships & programs.

  1. BASE — Black in AI Safety and Ethics

    Fellow, Governance Track

    Selected for the inaugural 13-week BASE Fellowship developing Black researchers and practitioners in AI alignment, security, and governance. Mentored capstone in AI governance.

  2. Clay AlphaForge

    GTM Engineering Bootcamp

    Inaugural cohort (18 selected out of 1,500 applicants). Four weeks building production GTM systems in Clay, with a portfolio of ~12 GTME projects.

  3. DataExpert.io

    Data & AI Engineering Certificate

    Data & AI Engineering Certificate (Zach Wilson cohort). Pipelines, data modeling, and applied AI patterns.

  4. BLCK VC

    Venture Fellow

    Developed investment theses across housing, energy, and aging sectors. Advised early-stage founders on product, GTM strategy, and AI integration.

  5. Terra.do

    Climate Fellow

    Built a climate action plan detailing opportunities in ocean carbon sinks and food-waste reduction as climate-mitigation levers.

Education / 05

Education

  1. University of Chicago

    Master of Public Policy (MPP), Data Science & Finance

  2. Colorado State University

    BS Business Administration, Supply Chain & CIS

Skills / 06

Skills

Build
Python, SQL, FastAPI, React, TypeScript, Postgres, pgvector, Azure Data Factory, Azure Synapse, Power BI, Excel/VBA, OpenAI / Claude / Gemini APIs, Claude Code, agent scaffolds, model evaluations
Deliver & Adopt
Customer-facing scoping, workflow design, deployment, change management, stakeholder synthesis, AI guardrails, training non-technical teams, Clay CRM, GTM systems
Domains
Housing, tax, climate / energy, legislative operations, M&A and deals technology, social impact, AI governance
Languages
English (native), Spanish (conversational)

Next / 07

Building useful AI where stakes are real.

Open to forward-deployed engineering, solutions engineering, data and AI engineering, partnerships, and GTM engineering roles — and to consulting engagements with teams trying to figure out what AI is actually worth building.