
SME Data Scientist Lead
Scott Afb, ILJob$140–180K/yrSeen 1w agoSeen in employer's feed today
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Job overview
SAIC seeks a Subject Matter Expert – Data Scientist Lead to support USTRANSCOM’s Joint Distribution Process Analysis Center at Scott AFB. The lead data scientist will advise on analytics strategy and cloud modernization, guide migration from legacy systems to Palantir and AWS, and develop models, pipelines, and decision-support tools for defense sustainment and global distribution. The role also leads and mentors an analytics team and collaborates with logistics stakeholders and cloud engineers.
Skills & qualifications
Skills
Qualifications
Full job description
Description
SAIC is seeking a Subject Matter Expert (SME) – Data Scientist Lead to support the U.S. Transportation Command (USTRANSCOM) Joint Distribution Process Analysis Center (JDPAC V) at Scott AFB, IL. This role serves as the lead data scientist and principal technical advisor guiding advanced analytics and data engineering initiatives across the Department of Defense (DoD) sustainment supply chain and global distribution enterprise.
As USTRANSCOM transitions its analytical backbone from legacy on-premises systems (Teradata) to modern cloud environments—including the Palantir / Maven Smart System and AWS / War Data Platform—the SME – Data Scientist Lead will spearhead the architecture, development, and operationalization of advanced analytical models and decision-support tools. This position blends technical leadership, hands-on data science, and stakeholder collaboration to deliver actionable intelligence for global mobility, deployment, and distribution operations.
Key Responsibilities:
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Technical Leadership & Cloud Modernization
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Serve as the lead data science SME, advising USTRANSCOM leadership and JDPAC stakeholders on analytic strategy, modern data architecture, and cloud adoption.
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Drive the migration of legacy analytic workflows and pipelines (Teradata) into enterprise cloud environments, primarily Palantir (Maven Smart System) and AWS (War Data Platform).
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Translate complex operational, distribution, and supply chain questions into rigorous mathematical models, predictive algorithms, and automated analytical pipelines.
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Data Engineering & Pipeline Development
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Design, implement, and govern data pipelines and ontologies across AWS and Palantir environments.
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Ingest, harmonize, and curate disparate, enterprise-scale logistics data from DoD transportation and supply data systems (including IGC and affiliated distribution feeds).
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Build robust data transformations and workflows utilizing modern cloud data tools and Power Automate to streamline recurring reporting processes.
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Data Science, Machine Learning & Operations Research
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Formulate and deploy advanced statistical, operations research, and machine learning addressing sustainment supply chain readiness, capacity constraints, and network distribution dynamics.
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Develop predictive and prescriptive capabilities, including:
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Multi-echelon supply and transportation demand forecasting
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Network and multimodal route optimization
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Port throughput and distribution bottleneck analysis
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Supply chain vulnerability, risk, and resilience modeling
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Deliver operational prototypes and simulation tools that evaluate time, cost, asset visibility, and mission trade-offs under dynamic operational conditions.
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Business Intelligence, Visualization & Automation
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Build and deliver interactive decision-support applications, dashboards, and exploratory tools using Palantir Workshop, Contour, Quiver, Qlik, Databricks, and Microsoft Power BI.
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Implement automated data alerts, workflows, and process integrations using Power Automate.
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Deliver high-impact executive briefings, technical documentation, and visual narratives to senior military and civilian leaders.
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Team Mentorship & Delivery Management
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Lead and mentor a team of data scientists, operations research analysts, and data engineers in modern analytics engineering, version control, and collaborative development best practices.
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Coordinate cross-functional requirements with functional logistics SMEs, data stewards, and cloud engineers in an agile delivery framework.
Qualifications
Required Qualifications:
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Clearance & Citizenship: Active DoD Secret clearance; U.S. Citizenship required.
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Education & Experience: Bachelor’s degree in Data Science, Operations Research, Mathematics, Statistics, Computer Science, Systems Engineering, or related technical field, with 10+ years of progressive experience in data science, advanced analytics, or operations research (or Master’s degree with 8+ years).
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Cloud & Data Systems:
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Demonstrated proficiency in SQL and relational database concepts, including experience with enterprise data architectures and migration patterns (e.g., Teradata to cloud repositories).
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Hands-on experience working in modern cloud analytical ecosystems such as AWS/Palantir.
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Programming & Modeling:
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Advanced proficiency in Python for data engineering, statistical modeling, and machine learning.
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Practical background applying linear/nonlinear optimization, simulation, network analysis, or predictive modeling to complex operational problems.
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BI & Visual Analytics:
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Proven experience building self-service dashboards and decision-support tools using Microsoft Power BI, Qlik, and/or cloud-native analytics platforms (e.g., Databricks, Palantir).
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Experience automating workflows and notifications using Microsoft Power Automate.
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Leadership & Communication:
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Demonstrated ability to lead technical teams, manage sprint backlogs, and convey advanced analytical concepts to non-technical operational stakeholders.
Desired Qualifications:
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Master’s or Ph.D. in Operations Research, Data Science, or Applied Mathematics.
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Hands-on experience within the Palantir / Maven Smart System ecosystem (Workshop, Contour, Quiver, Foundry/Ontology management).
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Hands-on experience with the AWS / War Data Platform ecosystem.
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Familiarity with DoD sustainment supply chain, joint deployment, and transportation systems (e.g., IGC, GATES, GDSS, CMOS, GFM, IBS).
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Experience deploying MLOps pipelines within DoD enterprise cloud environments.
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Agile certifications or experience leading data science efforts within Agile/DevSecOps frameworks.
Target salary range: $140,001 - $180,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.
REQNUMBER: 2618280
SAIC is a premier technology integrator, solving our nation's most complex modernization and systems engineering challenges across the defense, space, federal civilian, and intelligence markets. Our robust portfolio of offerings includes high-end solutions in systems engineering and integration; enterprise IT, including cloud services; cyber; software; advanced analytics and simulation; and training. We are a team of 23,000 strong driven by mission, united purpose, and inspired by opportunity. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $6.5 billion. For more information, visit saic.com. For information on the benefits SAIC offers, see Working at SAIC. EOE AA M/F/Vet/Disability
How this job compares
Set against the 5,365 open Data Scientist jobs on Olive Jobs, counted October 31, 2026.
- Pay
- This posting$140–180K/yr
- Illinois median$120–187K/yr131 salary ranges
- US median$135–215K/yr4,186 salary ranges
This range's midpoint, $160K, is 3% above the Illinois median midpoint ($156K) — in the middle half of Data Scientist salary ranges in Illinois.
- Openings
- Olive Jobs lists 149 open Data Scientist jobs in Illinois and 5,365 across the US. 6% of them nationwide are listed as remote or flexible.
- Hiring the most in Illinois
- Deloitte19 open
- Capital One12 open
- PwC12 open
- Experience
- This posting asks for at least 8 years of experience — more than three in four Data Scientist postings that state a minimum ask for (median 5 years, across 4,629 postings).
- Education
- 2,810 of the 5,365 open Data Scientist jobs (52%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 31, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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