Anees Amjad

I build AI tools and data products for real-world decisions.

I’m a master’s student in Computational Analysis and Public Policy at the University of Chicago. I build AI workflows, data pipelines, and software across energy, public service, and research.

Explore selected work Get in touch

Open to AI engineering roles, startup opportunities, and collaboration.

Build walkthrough

PublicPath

Making public-sector opportunities easier to find.

I co-built PublicPath, a platform helping students and early-career candidates explore government careers. My work focused on API ingestion and data quality: cleaning, deduplicating, normalizing, and validating listings for search and filtering.

Role
Co-founder, Engineering and Data; one of two engineers
Tools
Python, GitHub Actions, Supabase, Postgres
Live
Project website (joinpublicpath.com) ↗ Job search was not loading when checked on 6 Oct 2026.
PublicPath homepage with the headline ‘Your path into public service starts here’.
Project homepage (team product), captured 6 October 2026.

How a listing gets onto the site

  1. Schedule my work

    A GitHub Actions workflow starts ingestion on a daily schedule.

    PurposeA scheduled daily run, rather than manual pulls

  2. Ingest my work

    Python code requests listings from external job APIs.

    ResultRaw listings, each in its source’s own format

  3. Normalize my work

    Each source’s fields are mapped into one shared listing format.

    ResultListings that can be compared and filtered together

  4. Clean and deduplicate my work

    Listings are cleaned, and duplicates of the same listing are collapsed where they are detected.

    PurposeFewer duplicate listings

  5. Validate my work

    Listings are checked before they are used for search and filtering.

    PurposeCatch malformed records before use

  6. Store platform

    Listings are written to Postgres on Supabase.

    ResultOne queryable table of listings

  7. Search and filter platform

    The site lets visitors search and filter the stored listings.

    PurposeListings visitors can search and filter

Contrasting builds

Three other systems, set against the same lens: what goes in, what I did, what comes out.

  • CLARITY

    Turning clinical notes into patient-friendly explanations.

    I built a Python pipeline for the CLARITY healthcare-AI project that converts de-identified clinical-note JSON into patient-friendly explanatory videos. The workflow automates narration, slide generation, and MP4 production using Microsoft Neural TTS.

    1. De-identified note (JSON)
    2. Explanatory content
    3. Narration and slides
    4. MP4 video

    Contrast
    Also an automated pipeline, but it ends in a video rather than a searchable table.

    Research Assistant, HOPE Lab, UChicago Booth. Conceptual sequence; clinical material is not public.

  • Ourea Brain

    Company knowledge, accessible through Slack.

    I built and deployed Ourea Brain, an internal AI assistant that brings company context into Slack. It connects information across Slack, Gmail, Google Docs, and meeting notes to help colleagues retrieve project context, identify owners, and follow up on decisions. The application runs on Google Cloud Run and uses Anthropic’s Claude API; an early live deployment answered a Slack question using meeting-note context.

    1. Question in Slack
    2. App on Google Cloud Run + Claude API
    3. Response in Slack

    Contrast
    Answers questions in Slack from internal company context, rather than publishing public listings.

    Builder · Agentic AI Intern, Ourea Energy. Built and deployed internally.

  • Energy Market Intelligence

    Weekly leadership updates.

    Built a weekly AI-assisted market-intelligence workflow that filtered 50+ recurring signals across energy storage, utilities, and data centers into leadership updates on competitors, investments, and partnerships.

    1. Recurring market signals
    2. Weekly AI-assisted filtering
    3. Leadership updates

    Contrast
    Runs weekly, uses AI-assisted filtering, and ends in a leadership update rather than a listings table.

    Ourea Energy. Internal.

  • Chicago Eviction Risk

    Built an interpretable machine-learning and geospatial workflow to explore eviction-risk patterns in Chicago.

  • Political Narrative Navigator (team project)

    Analyzed 2,000+ presidential campaign speeches alongside YouGov data using AI-assisted text workflows. Political Narrative Navigator on GitHub ↗

Background

I combine software building with applied research: data platforms and AI workflows, alongside machine learning, survey analysis, and geospatial work.

  • Ourea Energy — Agentic AI Intern 2026–
  • Financial Health Network — Research Intern 2026–
  • HOPE Lab, UChicago Booth — Research Assistant 2026–
  • PublicPath — Co-founder 2026–
  • PAMS — Research Associate, ML 2025
  • CERP — Analyst 2024–25
  • UChicago — MS, Computational Analysis and Public Policy exp. 2027
  • Lahore School of Economics — BS, Economics and Political Science 2024