SCRM Data & Analytics Lead for Enterprise Risk

LMI Consulting, LLC; Arlington (VA); On-site; USD 120,000 - 185,000; Full time

Job summary

LMI Consulting, LLC seeks a Supply Chain Risk Management Data Lead in the US-VA Arlington area to design, develop, and implement enterprise SCRM analytics and data pipelines. You will bridge policy and technical execution, translating risk frameworks into data-driven dashboards and decision-support tools.

The role requires 7+ years in data engineering/science, proficiency in Python or R, SQL, and experience with enterprise data warehouses. Must hold a Top Secret clearance and US citizenship.

Qualifications

• Undergraduate degree in a quantitative discipline.
• 7+ years in data engineering/science, analytics, or quantitative modeling.
• Proficiency in Python, R, or similar languages.
• Experience building data pipelines and ETL/ELT processes.
• Proficiency with SQL and data warehouse architectures.
• Experience modeling and risk scoring; analytics leadership.
• Dashboards in Tableau/Power BI or equivalent.

Responsibilities

• Design, develop, and maintain data pipelines across multiple data sources.
• Define data schemas, governance, and quality processes for enterprise SCRM analytics.
• Develop quantitative risk models, supplier scoring, and segmentation frameworks.
• Apply NLP to extract risk signals from unstructured sources.
• Create modeling/simulation frameworks to assess disruption scenarios and wargaming tools.
• Build executive-ready dashboards and automated reporting for SCRM risk posture.

Skills

Python

R

SQL

Data analysis

Data storytelling

Education

Bachelor’s degree in a quantitative field

Tools

Snowflake

Databricks

Redshift

Synapse

Tableau

Power BI

AnyLogic

Job description

LMI Consulting, LLC seeks a Supply Chain Risk Management Data Lead in the US-VA Arlington area to design, develop, and implement enterprise SCRM analytics and data pipelines. You will bridge policy and technical execution, translating risk frameworks into data-driven dashboards and decision-support tools.

The role requires 7+ years in data engineering/science, proficiency in Python or R, SQL, and experience with enterprise data warehouses. Must hold a Top Secret clearance and US citizenship.