Senior Program Analyst, Data Products & AI; NCS - Mayor's Office of and Innovation

Senior Program Analyst, Data Products & AI (NCS) – Mayor's Office of Performance and Innovation

GRANT-FUNDED POSITION

TERM APPOINTMENT NOT TO EXCEED December 31, 2026

Salary Range: $88,715.00 - $ Annually

Starting Pay Range: $88,715.00 - $ Annually

THIS IS A NON-CIVIL SERVICE POSITION

NOTE: GRANT FUNDED POSITIONS ARE NOT ELIGIBLE FOR RETIREMENT BENEFITS

The Senior Program Analyst, Data Products & AI is a hybrid analytics-and-builder role within the Director’s Office. This position leads data and analytics projects on behalf of city agencies and the Mayor’s Office, moving from problem framing to analysis to decision-ready deliverables and durable tools. The role blends applied analytics and statistical modeling, data products and lightweight applications, integrations and automation, and AI proof-of-concepts (POCs) that are safe, evaluated, and operationally relevant.

The analyst partners closely with the Baltimore Design Lab, Citi Stat team, and works directly with agency staff to translate operational questions into clear measures, actionable insights, and usable tools.

• Lead rapid‑turn analyses for agencies and OPI leadership by framing questions, defining measures, establishing baselines, and translating findings into clear recommendations.
• Develop reproducible analyses using Python and SQL, including feature engineering, descriptive and inferential statistics, and predictive modeling where appropriate.
• Build analyses and visuals using BI, GIS and related analytics products.
• Produce dashboards and data products to support operations research and analytics.
• Design and execute AI POCs for city use cases, with clear success measures and baseline comparisons.
• Develop evaluation plans for AI POCs, test failure modes, and produce clear go/no‑go recommendations that address value, risk, and operational fit.
• Conduct operational, policy, and program analyses using administrative data (including 311, permitting, water billing, housing, inspections), clearly communicating assumptions, uncertainty, and limitations.
• Translate technical outputs into clear briefings, visuals, and decision materials for executive leadership, Citi Stat sessions, and agency partners as appropriate.

• Build decision‑ready products such as dashboards, parameterized reports, reusable datasets, and lightweight web applications that surface analytic outputs and progress against targets.
• Build and maintain simple internal tools and UIs and partner with engineers to product ionise and scale when needed.
• Develop and support data integrations (APIs, extracts, automation patterns) in collaboration with platform and engineering staff so analytic products can be sustained.
• Maintain code, notebooks, queries, and documentation in shared repositories with clear READMEs and reproducible methods.
• Create reusable templates (analysis plans, model evaluation notes, dashboard specifications, data dictionaries) to accelerate delivery across future requests.
• Support lightweight project leadership across ad‑hoc engagements, including milestones, dependencies, risks, and close‑the‑loop follow‑up with stakeholders.

• Lead lightweight discovery with agency teams and end users (frontline staff, supervisors, analysts, program owners) to clarify the problem, map workflows, document requirements, and define success measures for analytics products and AI POCs.
• Conduct targeted user engagement activities including interviews, observation/shadowing, short surveys, and structured feedback sessions to validate assumptions and ensure tools reflect operational reality.
• Facilitate working sessions with stakeholders to review prototypes (dashboards, internal tools, model outputs), incorporate feedback, and drive adoption through iterative improvement.
• Translate user needs into clear product artifacts (problem statements, user stories, functional requirements, data requirements, and acceptance criteria) and partner with engineering/platform teams to deliver and scale solutions.
• Develop enablement materials that support sustained use (quick‑start guides, training decks, office hours,…