Senior Data Scientist & AI Engineer

Richard L. Duchossois Foundation•Chicago, IL

7h•Hybrid

About The Position

RLD Foundation seeks a mission-driven Senior Data Scientist & AI Engineer to join our Data Strategy & Insights team. In this role, you will play a central part in advancing the foundation’s data strategy in a highly collaborative environment. The position sits at the intersection of data and AI engineering, advanced analytics, and data strategy, offering the opportunity to do technically rigorous, high-impact work in service of social change. The role has two co-equal primary responsibilities: (1) building and owning RLD Foundation’s core data infrastructure and AI-enabled analytics platform, and (2) conducting advanced analytics to generate insights that inform grantmaking strategy and organizational learning. The position will architect the technical systems that enable high-quality data work across the foundation while also serving as a lead analyst who delivers clear, actionable insights to program teams and leadership. There will also be opportunities to contribute to broader data strategy development and selective grantee- and field-facing data capacity building initiatives. You will report to the Director of Data Strategy & Insights and work alongside a Senior Research and Insights Analyst, with the potential for the team to grow as the organization evolves. This is an early-stage data environment with significant opportunity to shape systems, tools, and analytical approaches. You will bring technical leadership to the team, with the autonomy to architect solutions and make strategic technical decisions that will define how the foundation uses data to catalyze meaningful change. We recognize this role asks for an uncommon combination of technical depth and mission commitment. The right candidate brings senior-level data engineering and analytics expertise and is equally energized by applying those skills to advance social good. If you're someone who could thrive in tech but would rather build systems that help families, veterans, and entrepreneurs in Chicago, this role offers that meaningful intersection.

Requirements

Typically 7+ years of experience in data science, engineering, analytics, AI, or related role
Mission alignment: Demonstrated commitment to social impact and the values of the Foundation
Data infrastructure: Experience with cloud data platforms (e.g., Snowflake, Azure, BigQuery, AWS), data warehouse architecture, and building automated ETL/ELT pipelines (e.g. dbt, Airflow)
Programming expertise: Advanced proficiency in SQL, and Python and/or R for data analysis, modeling, and automation
Data analytics and modeling: Strong foundation in statistical methods, predictive modeling, and machine learning; experience applying these methods to real-world problems
Practical experience with modern AI/ML concepts (LLMs, embeddings, transformers); experience applying AI/ML methods to real problems.
Communication: Ability to explain complex concepts clearly and patiently, adapting to match individual learning needs
Technical versatility: Comfortable learning new tools, technologies, and working across the data stack
Version control: Proficiency with Git/GitHub for collaboration and code management

Nice To Haves

8-10+ years of experience and/or an advanced degree in data science, engineering, analytics, AI, or related role
Experience in civic technology, nonprofit organizations, philanthropy, or government
Exposure to working with vector databases, embeddings, or modern document stores
Experience integrating structured and unstructured data for analysis
Familiarity with responsible AI, model evaluation, and human-in-the-loop workflows
Experience building web-based data products or interactive applications (dashboards, data explorers, mapping tools)
Experience providing technical assistance or data capacity support to external partners
Experience strengthening data ecosystems or collaborative data infrastructure across multiple organizations
Knowledge of data governance, privacy, and ethics frameworks
Demonstrated ability to work as part of a team and with people who hold diverse perspectives
Highly developed emotional intelligence and demonstrated ability to use interpersonal skills and political acumen in respectful and collaborative ways
Flexibility, commitment to teamwork, curiosity, and a sense of humor
Capacity to work amicably in a small office with high volume of work, as well as a deep sense of responsibility and accountability
Ability to make decisions, justify recommendations and be responsible and clear with stakeholders
A record of recognizing and acting on opportunities to continuously improve
High degree of professional ethics and integrity
Ability to work autonomously

Responsibilities

Lead the development and maintenance of modern and scalable data infrastructure to undergird RLD Foundation's data strategy and AI-enabled knowledge platform
Architect and maintain RLD Foundation’s cloud-based data infrastructure, ensuring performance, scalability, and security
Develop and automate ingestion and transformation pipelines to build an integrated warehouse of data from internal systems (grants management, CRM, program data) and external sources (public APIs, data partners, research institutions, government)
Support the development of analytical tools and web-based platforms that enable staff, board, and ecosystem partners to access real-time insights
Implement rigorous data quality, validation, and governance protocols
Develop data dictionaries, and document all code and data processing workflows
Collaborate with the Data Team and Program Directors to develop an institutional data practice where we ask powerful questions, collect relevant data, generate insights, and take action
Apply statistical, machine learning, and geospatial techniques for applied analysis, with advanced NLP and LLM-based methods primarily used within the AI-enabled knowledge platform
Creatively source and curate relevant datasets from public, private, academic, and alternative sources relevant to RLD Foundation’s work and to fill sector data gaps
Conduct exploratory data analysis across RLD Foundation’s internal and partner datasets to identify trends, gaps, and opportunities
Advise on key data points for data briefs and white papers that share insights transparently with grantees and the broader sector
Lead the design and development of an AI-enabled knowledge layer, in collaboration with external partners as appropriate, that integrates structured data (grants, finances, open data, acquired private data) and unstructured data (reports, research, meeting notes, transcripts), into a unified, query-able system
Build retrieval-augmented generation (RAG) pipelines that allow staff to ask complex strategy questions and receive synthesized, source-grounded answers (i.e. “What strategies have been most effective in creating family-sized affordable housing in Chicago, and where do gaps remain?”)
Implement metadata, embeddings, and document indexing to support semantic search, cross-dataset linking, and transparent sourcing
Partner with program teams to translate learning and strategy questions into AI-supported workflows and analytical products
Ensure responsible AI practices, including data governance, bias awareness, privacy protection, and explainability of outputs
Partner with the Director of Data Strategy & Insights, Program Directors, Grants Manager, and Research Analysts to identify datasets to acquire and analyses to conduct that support strategic learning, monitoring, and evaluation priorities
Contribute to the design and tracking of indicators and metrics that can help RLD Foundation better understand baselines, progress and trends in its focus issue areas
Collaborate across the organization to ensure all data collection systems and tools are thoughtfully designed to capture information that aligns with organizational needs and learning questions
Contribute to a culture of iterative learning around data use
Work with select grantees to understand their data aspirations, current pain points, and where RLD Foundation support could help them build data capacity
Partner with grantees and capacity-building vendors to shape and support data initiatives; provide hands-on support selectively when it creates high leverage for learning or infrastructure
Contribute analysis and expertise to collaborative initiatives that enable grantees, peer funders, and others to learn together from data
Create public-facing data tools and resources for grantees and the broader field