Skip to content
ACT1 Federal

Senior Data Scientist – Defense Industrial Base (DIB) & Manufacturing Analytics

Arlington, VA; ArlingtonUnited States
Senior · TASC
POSTED 21 SEPTVERIFIED 1D AGO
Apply Ask
Role
48 days opentrue age
Posted 21 Sept
Payin text
$170k–200kposted
▲ +18% vs market median $157k
$134k$200k
Market p25–p75
$134k–$180k
Washington DC · n=16 · 365d to 6 Nov
CompanyACT1 Federal →
49open roles
Opened · 30d
+1
Closed · 30d
−4
5d of snapshots · 30d window
Market
1,766open · Senior Analytics / Data science
Opened · 7d
+1056% of open
All analytics / data science
7,737open
All tracked boards · live 9 Nov · n=1,766

Position Title: Senior Data Scientist – Defense Industrial Base (DIB) & Manufacturing Analytics

Location: Arlington, Virginia

Category: Funded

Schedule (FT/PT): Full Time

Travel Required: N/A

Shift: Day

Remote Type: Hybrid

Clearance required: Top Secret clearance required

Salary: $170,000 - $200,000

Who is ACT1 Federal? ACT1 Federal LLC is a 100% employee-owned company. We’ve served the Department of War (DoW) for nearly thirty years. Our core missions include weapon systems engineering, logistics, space domain expertise, global defense and security, business and financial management for security assistance and major defense articles, as well as military training and arctic security. Join us!

Description: ACT1 Federal is seeking an experienced Senior Data Scientist – Defense Industrial Base (DIB) & Manufacturing Analytics will identify, evaluate, pilot, and govern targeted AI, machine-learning, operations-research, optimization, forecasting, and advanced-analytics applications.

Responsibilities

Manufacturing Data Science and Analytics

  • Integrate and analyze production, supplier, schedule, quality, capacity, financial, and program data to identify constraints, trends, dependencies, and emerging risks affecting weapon-system output.
  • Develop analytical models, dashboards, forecasts, and leading indicators for throughput, cycle time, lead time, backlog, yield, on-time delivery, supplier performance, and capacity.
  • Apply statistical analysis, machine learning, AI, anomaly detection, forecasting, optimization, and other advanced methods where appropriate to support production-recovery and supplier-capacity decisions.
  • Assess data quality, completeness, lineage, comparability, access, and analytical limitations; distinguish validated evidence from assumptions, incomplete reporting, and unsupported claims.

Decision Support and Advanced Analytics

  • Develop repeatable analytical methods and decision-support products that help TASC prioritize constraints, interventions, investments, supplier actions, and production-recovery initiatives.
  • Evaluate proposed interventions and investments using quantitative measures of expected capacity, throughput, schedule, cost, quality, resilience, and mission impact.
  • Identify critical data gaps and recommend practical collection, normalization, governance, and validation approaches needed to improve analytical confidence and decision quality.
  • Develop scenario, sensitivity, trend, and predictive analyses to illuminate tradeoffs, dependencies, likely bottlenecks, and potential consequences of alternative courses of action.
  • Support data reviews, technical working sessions, and analytical engagements with program offices, production facilities, prime contractors, suppliers, and other authorized stakeholders.

TASC Team Integration and Decision Support

  • Serve as the senior data science, AI, and advanced analytics advisor to the TASC team for assigned PAE and weapon-system priorities.
  • Integrate analytical findings with production, schedule, supplier, engineering, quality, investment, and program data to develop executable courses of action.
  • Coordinate analytical requirements and findings across DASN DIB, PAEs, program offices, systems commands, engineering, cybersecurity, contracting, financial management, production facilities, and industry stakeholders.
  • Prepare dashboards, analytical assessments, forecasts, issue papers, decision briefings, action plans, and recommendations for senior Government leadership.

Requirements

  • Bachelor's degree from an accredited institution in data science, statistics, mathematics, engineering, computer science, operations research, analytics, or a related discipline.
  • 10+ years’ experience in data science, advanced analytics, operations research, AI/machine learning, manufacturing analytics, or a closely related field.
  • Demonstrated experience applying quantitative analysis to complex manufacturing, production, supply-chain, industrial-base, or defense problems.
  • Experience with predictive models, forecasts, dashboards, performance indicators, statistical analyses, or optimization tools using complex operational data.
Source · ACT1 FederalFirst seen 4 NovOriginal ↗