Talent That Goes
Beyond Good Data

The Illinois Power Agency is leading Illinois' transition to renewable energy — and needed a solution to make the state's progress visible, accessible, and actionable for policymakers, stakeholders, and the public.

The Fellow identified a data discrepancy that had excluded certain communities from accessing an important benefit - an environmental justice designation - which is critical for ensuring a fairer distribution of environmental benefits and burdens in investments. The Fellow also built three Tableau dashboards covering utility-scale procurements, Midwest generation, and Midwest capacity, alongside a dataset tracker to strengthen IPA's data infrastructure for the long-term.

IPA now has a live, public-facing view of Illinois' clean energy progress. The data correction ensured affected communities began receiving the environmental justice benefits they were entitled to — a meaningful win for both the agency's mission and the communities it serves.

CamoAG is a sales and marketing intelligence platform for agriculture — and needed to strengthen its data infrastructure to power executive dashboards, improve its ML-based land valuation model, and enhance its customer-facing AI agent with better context and accuracy.

Built and optimized SQL views and joins across Snowflake and dbt to create aggregated datasets powering executive dashboards used in weekly all-hands meetings. Enriched the AI agent's context documentation and yml pipeline files, significantly improving response accuracy. Defined metrics to validate the ML-based land valuation model, and created user analytics databases segmented by device type, persona, and organization.

Leadership now has reliable, live dashboards informing weekly strategy decisions across divisions. The AI agent gives clearer, more accurate responses to clients. And the data infrastructure — from pipeline documentation to validated model metrics — is more robust and scalable, positioning CamoAG for its next phase of growth in precision agriculture.

Cook County Health's Nursing Innovation team wanted to use data to improve patient outcomes, track the impact of over 100 nursing research projects, and build a culture of recognition across a workforce of hundreds of nurses.

Built a patient mobility predictive model using clinical data — cleaning over 200,000 records and achieving 95% model convergence — then submitted findings as a Vizient research abstract. Created an interactive D3.js Nursing Research Dashboard tracking 100+ projects with ROI estimation, and developed a Recognition App adopted by 600 employees. Automated reporting pipelines with Power Automate, saving 10 hours of manual work per month.

Nursing leadership can now see the cost and impact of every research project in one place, with $100K in potential annual savings identified through the ROI model. The predictive mobility model strengthens quality-of-care analyses tied to patient length of stay. And the Recognition App has become a cornerstone of staff morale across the health system.

Cook County Health's Office of the Chief Data Officer needed to bring structure and consistency to its analytics ecosystem — standardizing how BI resources were built, requested, and shared across a large, complex public health system.

Designed and launched a new BI Request Process from the ground up — building intake forms, automating workflows, and communicating the rollout to over 1,000 employees. Standardized Tableau reference pages across 20+ dashboards, produced a monthly Data Digest newsletter, facilitated monthly Tableau training sessions, and led full BI team meetings during a leadership transition. Used Python to automate provider ID mapping and validate data quality across systems.

CCH now has a repeatable, documented BI intake process that reduced redundant requests and streamlined analytics operations. Dashboard standardization improved data consistency across the health system. Teams across the organization can now independently access, understand, and act on data — a foundational shift toward data literacy at scale.

The Opportunity Finance Network — the leading national network of Community Development Financial Institutions — needed to build a centralized data warehouse to consolidate disparate data sources and enable better-informed decisions about where to direct capital for underserved communities.

Led the provisioning and standup of OFN's first data warehouse on Microsoft Azure, coordinating between internal IT, the data team, and external consultants to navigate platform permissions and infrastructure setup. Simultaneously launched a comprehensive data dictionary project to document and standardize data definitions across the organization, laying the foundation for consistent reporting and governance.

OFN now has the infrastructure to ingest, organize, and query its data in one place — a critical step toward enabling the network to measure impact, allocate resources, and advocate for community lending at a national scale. The data dictionary ensures that as data flows into the warehouse, every team speaks the same language.

The National Community Investment Fund — a leading CDFI intermediary — wanted to modernize how it analyzes and reports on community development financial institutions, replacing fragmented tools with a unified, AI-powered analytics platform that could serve both internal teams and external stakeholders.

Designed and built the BankImpact AI platform from the ground up — a ChatGPT-style analytics interface integrating Advanced Search, Historical Analytics, and Peer Builder tools into a single React frontend backed by real-time API endpoints. Developed automated Wall Street-style PDF reports with institution metrics, SPMM components, and AI-generated narrative summaries. Reported directly to the CEO, iterating weekly on design and functionality.

NCIF now has a production-ready analytics platform that lets non-technical staff query CDFI data conversationally and generate professional reports on demand. The tool consolidates what previously required multiple systems into one coherent experience — accelerating how the organization tracks outcomes, compares peer institutions, and communicates impact to investors and policymakers.

The Cook County Justice Advisory Council invests in organizations working to reform the criminal justice system. JAC wanted to build infrastructure to measure the collective impact of its investments across its grantee portfolio and target resources more effectively.

Designed and implemented a new metric approval process to standardize what grantees submit, facilitated Notice of Funding Opportunity application review panels, and produced geographic impact reports showing where proposed grantees operate across Cook County's community areas.

JAC now has a consistent, repeatable framework for grantee reporting — enabling the council to compare outcomes across programs, track progress toward shared goals, and make the case for systemic change in Cook County's criminal justice system.

Cook County's Department of Human Rights and Ethics is responsible for enforcing civil rights protections across the county — and wanted to build the data systems to track casework, measure outcomes, and understand where their work was having the greatest impact.

Built the department's first CRM from the ground up, migrated it to Salesforce, standardized all departmental metrics into a comprehensive tracking system, and created GIS maps to visualize the geographic distribution of Human Rights Act complaint data.

The department can now track every complaint from intake to resolution, report on outcomes with consistent metrics, and see where enforcement activity is concentrated — giving leadership the foundation to make data-driven decisions and demonstrate their impact across Cook County.

The American Association for the Advancement of Science was investing in modernizing its data infrastructure — and wanted to give its Editorial and Publishing teams real-time visibility into content performance to support faster, better-informed decisions.

Expanded the Content Tracking System into a Power BI dataset with two auto-refreshing reports for Editorial and Publishing, piloted a new AWS-based data platform by building and presenting a connected report to stakeholders, and wrote Python scripts to automate the platform transition.

Two teams now work from live, auto-refreshing dashboards instead of static reports — improving visibility and decision-making speed. The AWS pilot earned strong stakeholder endorsement and laid the groundwork for AAAS's next phase of data infrastructure investment.

CASEL had accumulated 500+ data sets evaluating social and emotional learning programs across the US — but no systematic way to compare curriculum effectiveness across districts.

Built custom R code to analyze and harmonize the full data warehouse, evaluating the effectiveness of 40+ SEL curricula and producing district-level Excel reports for 20 partner districts.

CASEL could for the first time show partners evidence-backed comparisons across programs — making their research more actionable and their curricula more accessible nationwide.

West Side United had an ambitious goal — cut the 16-year life expectancy gap between Chicago's Loop and West Side neighborhoods by 50% by 2030 — but lacked data infrastructure to connect health outcomes to their economic interventions.

Built an analytical framework linking cancer outcomes to neighborhood-level economic and social factors, giving West Side United a data-driven lens to target and measure their grant-making.

The Fellow's analysis directly informed grant proposals that secured $725K in small business grants — a 7.5% increase over the prior year — reaching 35 grantees on the West Side.