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HomeCompaniesCareers Lmi Icims ComSupply Chain Risk Management Data Lead - (Clearance Required)

Supply Chain Risk Management Data Lead - (Clearance Required)

Careers Lmi Icims Com · Washington, DC, DC, US · Active · iCIMS

Job facts

FieldValue
CompanyCareers Lmi Icims Com
TitleSupply Chain Risk Management Data Lead - (Clearance Required)
Normalized title-
Department / teamMG - Markets and Growth - MG - Navy
LocationWashington, DC, DC, United States
Work model-
Employment typeOTHER
Salary-
Statusactive
ATS provideriCIMS
Posted / first seen2026-06-01 / 2026-06-02
Changed / last seen2026-06-03 / 2026-06-06

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City jobsActive postings in Washington, DC.Open
Department jobsActive postings in MG - Markets and Growth - MG - Navy.Open
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Linked records

CompanyCareers Lmi Icims Com
Source3f14ba88-ea78-4c23-a7d0-93666b5dea5d
ATS provideriCIMS

Description

Overview LMI is seeking a Supply Chain Risk Management (SCRM) Data and Analytics Lead to support the design, development, and implementation of an enterprise SCRM organization for a client in the Washington, DC metro area. The ideal candidate bridges SCRM policy and technical execution, with practitioner-level expertise in data engineering, data science, analytics, and modeling and simulation applied to supply chain risk contexts. This role serves as the technical counterpart to our SCRM strategy and policy capability, translating risk frameworks and business requirements into data pipelines, analytical models, dashboards, and decision-support tools that enable enterprise-wide SCRM operations. LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed. Headquartered in Tysons, Virginia, LMI serves the defense, space, healthcare, and energy sectors. Responsibilities Responsibilities may include: Design, develop, and maintain data pipelines that ingest, integrate, and transform supplier, contract, financial, and threat intelligence data from disparate internal and external sources. Define and implement data schemas, governance structures, and quality processes that support reliable, auditable SCRM analytics and reporting at enterprise scale. Develop quantitative supplier risk scoring models, criticality assessments, and risk segmentation frameworks using statistical and machine learning methods. Apply NLP and text analytics to extract risk signals from unstructured sources including news feeds, regulatory filings, and threat intelligence reports. Design and develop modeling and simulation frameworks to assess supply chain disruption scenarios, single-point-of-failure risks, and mitigation trade-offs, including scenario-based tools to support wargaming and executive decision-making. Build and maintain executive-ready dashboards, geospatial visualizations, and automated reporting pipelines that communicate SCRM risk posture clearly and actionably. Partner with SCRM strategy and policy experts to translate risk frameworks and governance requirements into technical data and analytical solutions. Define technical requirements for SCRM tools, platforms, APIs, and data integrations and support vendor evaluation and capability assessments. Facilitate working sessions with acquisition, cybersecurity, IT, data, and mission operations stakeholders to define data requirements, reporting needs, and analytical use cases. Prepare technical documentation, data dictionaries, model methodology briefs, and decision-ready products for both technical and senior non-technical audiences. Qualifications MINIMUM QUALIFICATIONS Undergraduate degree required; quantitative discipline preferred (data science, computer science, statistics, mathematics, operations research, or systems engineering). Seven (7) or more years of relevant experience in data engineering, data science, analytics, or quantitative modeling. Proficiency in Python, R, or similar languages for data manipulation, statistical analysis, and model development. Experience building and deploying data pipelines, ETL/ELT processes, or data integration solutions in enterprise environments. Proficiency with SQL and familiarity with data warehouse or data lake architectures (e.g., Snowflake, Databricks, Redshift, Synapse, or equivalent). Demonstrated experience developing quantitative risk models, supplier scoring frameworks, or anomaly detection capabilities. Experience designing and building dashboards and data visualizations in Tableau, Power BI, or equivalent platforms. Familiarity with SCRM concepts including supplier risk assessment, third-party due diligence, supplier segmentation, and criticality analysis. Strong written and verbal communication skills; ability to produce technical documentation and translate analytical findings into executive-ready outputs. Active TOP SECRET clearance required. Must be a U.S. citizen. PREFERRED QUALIFICATIONS Experience with M&S tools or frameworks (e.g., AnyLogic, Simio, Arena, agent-based modeling platforms, or custom Python/R stochastic simulation development). Familiarity with federal SCRM policy frameworks including NIST SP 800-161, DFARS 252.204-7012, and related DoD acquisition risk guidance. Experience working in or supporting DoD or federal agency data environments, including familiarity with data classification, access controls, and ATO/RMF processes. Knowledge of graph analytics or geospatial analysis methods applied to supplier network mapping and geographic concentration risk. Familiarity with commercial supply chain risk data providers (e.g., Exiger, Sayari, Dun & Bradstreet) or open-source threat intelligence tools. EEO Statement LMI is an Equal Opportunity Employer, where all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

Full job record

Job IDd74a90c5554b8071166bd79e1b75c7a1331d5658
Org ID59a8d2dd-5934-4e7f-a3c3-9c46636da829
Source ID3f14ba88-ea78-4c23-a7d0-93666b5dea5d
Board ID3f14ba88-ea78-4c23-a7d0-93666b5dea5d
Providericims
Provider Job Key14127
TitleSupply Chain Risk Management Data Lead - (Clearance Required)
Normalized Title
Statusactive
Activeyes
Location TextWashington, DC, DC, US
DepartmentMG - Markets and Growth - MG - Navy
Team
Employment TypeOTHER
Workplace Type
Remote Policy
CountryUnited States
RegionDC
CityWashington, DC
Salary RawOverview LMI is seeking a Supply Chain Risk Management (SCRM) Data and Analytics Lead to support the design, development, and implementation of an enterprise SCRM organization for a client in the Washington, DC metro area. The ideal candidate bridges SCRM policy and technical execution, with practitioner-level expertise in data engineering, data science, analytics, and modeling and simulation applied to supply chain risk contexts. This role serves as the technical counterpart to our SCRM strategy and policy capability, translating risk frameworks and business requirements into data pipelines, analytical models, dashboards, and decision-support tools that enable enterprise-wide SCRM operations. LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed. Headquartered in Tysons, Virginia, LMI serves the defense, space, healthcare, and energy sectors. Responsibilities Responsibilities may include: Design, develop, and maintain data pipelines that ingest, integrate, and transform supplier, contract, financial, and threat intelligence data from disparate internal and external sources. Define and implement data schemas, governance structures, and quality processes that support reliable, auditable SCRM analytics and reporting at enterprise scale. Develop quantitative supplier risk scoring models, criticality assessments, and risk segmentation frameworks using statistical and machine learning methods. Apply NLP and text analytics to extract risk signals from unstructured sources including news feeds, regulatory filings, and threat intelligence reports. Design and develop modeling and simulation frameworks to assess supply chain disruption scenarios, single-point-of-failure risks, and mitigation trade-offs, including scenario-based tools to support wargaming and executive decision-making. Build and maintain executive-ready dashboards, geospatial visualizations, and automated reporting pipelines that communicate SCRM risk posture clearly and actionably. Partner with SCRM strategy and policy experts to translate risk frameworks and governance requirements into technical data and analytical solutions. Define technical requirements for SCRM tools, platforms, APIs, and data integrations and support vendor evaluation and capability assessments. Facilitate working sessions with acquisition, cybersecurity, IT, data, and mission operations stakeholders to define data requirements, reporting needs, and analytical use cases. Prepare technical documentation, data dictionaries, model methodology briefs, and decision-ready products for both technical and senior non-technical audiences. Qualifications MINIMUM QUALIFICATIONS Undergraduate degree required; quantitative discipline preferred (data science, computer science, statistics, mathematics, operations research, or systems engineering). Seven (7) or more years of relevant experience in data engineering, data science, analytics, or quantitative modeling. Proficiency in Python, R, or similar languages for data manipulation, statistical analysis, and model development. Experience building and deploying data pipelines, ETL/ELT processes, or data integration solutions in enterprise environments. Proficiency with SQL and familiarity with data warehouse or data lake architectures (e.g., Snowflake, Databricks, Redshift, Synapse, or equivalent). Demonstrated experience developing quantitative risk models, supplier scoring frameworks, or anomaly detection capabilities. Experience designing and building dashboards and data visualizations in Tableau, Power BI, or equivalent platforms. Familiarity with SCRM concepts including supplier risk assessment, third-party due diligence, supplier segmentation, and criticality analysis. Strong written and verbal communication skills; ability to produce technical documentation and translate analytical findings into executive-ready outputs. Active TOP SECRET clearance required. Must be a U.S. citizen. PREFERRED QUALIFICATIONS Experience with M&S tools or frameworks (e.g., AnyLogic, Simio, Arena, agent-based modeling platforms, or custom Python/R stochastic simulation development). Familiarity with federal SCRM policy frameworks including NIST SP 800-161, DFARS 252.204-7012, and related DoD acquisition risk guidance. Experience working in or supporting DoD or federal agency data environments, including familiarity with data classification, access controls, and ATO/RMF processes. Knowledge of graph analytics or geospatial analysis methods applied to supplier network mapping and geographic concentration risk. Familiarity with commercial supply chain risk data providers (e.g., Exiger, Sayari, Dun & Bradstreet) or open-source threat intelligence tools. EEO Statement LMI is an Equal Opportunity Employer, where all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://careers-lmi.icims.com/jobs/14127/supply-chain-risk-management-data-lead---%28clearance-required%29/job
Apply URLhttps://careers-lmi.icims.com/jobs/14127/supply-chain-risk-management-data-lead---%28clearance-required%29/job
First Seen At2026-06-02 13:09:36Z
Last Seen At2026-06-06 20:01:41Z
Last Checked At2026-06-06 20:01:41Z
Last Changed At2026-06-03 14:05:31Z
Inactive At
Source Posted At2026-06-01 04:00:00Z
Source Updated At2026-06-01 17:34:33Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=icims/board=careers-lmi.icims.com/date=2026-06-06/2026-06-06T20-01-33-761Z-592404f8e63b23769ff422f948eaf3215b7b08cf167e959757f94f748a68f43a.json
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