Lead Data Scientist — Automated Performance Analysis (TS/SCI)

Zaden Technologies, Inc.; Denver (CO); On-site; USD 140,000 - 175,000; Full time

Benefits offered by this job

401k employer contributions

Health insurance 50% coverage

Job summary

Zaden Technologies is hiring a Senior Data Scientist / Analysis Lead to head the independent analysis function on a ground data processing modernization effort supporting a national security space mission. This is an on-site position in Aurora, CO with an anticipated January 2027 start.

You will design baseline captures, build automated analysis pipelines, define metrics and evidence standards, and present findings to leadership while mentoring data engineers as the team grows.

Qualifications

• 7+ years in data science, quantitative analysis, or test and evaluation for complex software or mission systems.
• Strong Python and data engineering skills (pandas or similar, SQL, data pipelines) and statistics fundamentals.
• Experience analyzing system or software performance data (latency, throughput, resource utilization) and automating that analysis.

Responsibilities

• Design and run baseline captures on legacy applications and replay comparisons against modernized builds.
• Build automated analysis pipelines that diff telemetry and generate performance/regression reports.
• Define metrics, thresholds, and evidence standards for migrated applications.
• Present independent findings to program leadership with defensible data.
• Mentor data engineers and test automation engineers as the team grows.

Skills

TS/SCI clearance

Python & data eng

Statistics basics

Performance data analysis

Independent verification

Tools

Pandas

SQL

CI/CD

Containerization

Job description

Zaden Technologies is hiring a Senior Data Scientist / Analysis Lead to head the independent analysis function on a ground data processing modernization effort supporting a national security space mission. This is an on-site position in Aurora, CO with an anticipated January 2027 start.

You will design baseline captures, build automated analysis pipelines, define metrics and evidence standards, and present findings to leadership while mentoring data engineers as the team grows.