Program Data Analyst: AI Use Cases & Data Prototypes

YDU JC Air Cond & Ref Inc.- Dubai

United States

On-site

USD 61,000 - 83,000

Full time

3 days ago

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Job summary

Johnson Controls is seeking a Program Data Analyst to transform messy project data into actionable insights for the Digital Enablement team in the United States. You will build structured outputs, run analyses, and prototype AI-driven solutions, collaborating with project teams, engineering, and sales to support delivery decisions.

The role requires a master's in a technical field, strong Python/SQL skills, API experience, and ability to deliver clear documentation.

Qualifications

Master's degree in engineering, data science, computer science, information systems, or a related technical field.
Demonstrated ability to process large, inconsistent datasets end to end, including extraction from documents and reconciliation across sources.
Proficiency in Python or an equivalent scripting language, advanced Excel, and SQL.
Experience calling and integrating APIs and building small automations without waiting for a development team.
Practical experience applying AI services to a real workflow, with sound judgment about where they do not fit.
Clear written communication and the discipline to document a method so it can be repeated and defended.

Responsibilities

Extract, clean, and normalize project data from documents, PDFs, scanned files, and spreadsheets.
Collect, validate, and consolidate data from multiple business systems and reporting sources.
Run quality checks, document assumptions and exclusions, and flag gaps before they reach a deliverable.
Build repeatable processing routines and structured outputs that reduce manual rework.
Maintain version control and file organization so the current source of truth is unambiguous.
Analyze prepared datasets to answer defined questions, including comparisons, benchmarking, trend analysis, and estimates.
Research external data sources, tools, and vendor capabilities, and summarize what is usable, what it costs, and where the limits are.
Produce recurring and ad hoc reports and create visualizations that communicate findings clearly to leadership.
Present findings and recommendations to project teams and cross-functional stakeholders.
Identify candidate AI use cases with business owners and assess feasibility, data readiness, and expected value before any build commitment.
Implement approved use cases using approved AI services and tooling, working within company data handling and governance requirements.
Validate output quality against a documented baseline and measure the effort saved against the manual process it replaces.
Track accuracy and adoption after release, and rework or retire use cases that do not hold up in day-to-day use.