Senior Data Analyst

Prolog Inc.•Alley, MO

8h•Onsite

About The Position

ProLog, Inc. is seeking a Senior Data Analyst to lead data analytics and predictive modeling efforts supporting the U.S. Army Aviation and Missile Command (AMCOM) Logistics Center (ALC) Supply Chain Management Directorate (SCMD) at Redstone Arsenal, Alabama. The Senior Data Analyst will serve as the technical lead for data mining, statistical modeling, machine learning, and business intelligence development. This position is responsible for transforming raw Army logistics data into advanced descriptive, predictive, and prescriptive models that optimize supply availability, reduce pipeline cycle times, and support AI-driven decision-making for defense supply chain leadership.

Requirements

Bachelor's degree in Data Science, Operations Research, Computer Science, Statistics, Mathematics, or a related quantitative field.
7 or more years of professional experience in data analytics, data science, or statistical modeling.
3 or more years of experience applying data analytics within a supply chain, logistics, or defense operational environment.
Demonstrated expertise in data mining, statistical analysis, predictive modeling, and machine learning techniques.
Advanced proficiency with visualization tools (Power BI, Tableau) and quantitative programming tools (Python, R, SQL).
Strong capability to communicate complex mathematical and analytical findings to non-technical executive stakeholders.
Ability to mentor and provide technical oversight to supporting junior data analysts.
Must possess or be eligible to obtain and maintain a SECRET security clearance eligibility.

Nice To Haves

Direct experience analyzing Army aviation, missile, or defense supply chain data structures.
Familiarity with Army enterprise data platforms (LMP, Vantage, AESIP, GCSS-Army).
Experience developing artificial intelligence (AI) or machine learning (ML) solutions for demand planning or inventory optimization.
Knowledge of big data technologies, cloud data environments (GCC High), and SQL database architectures.
Experience supporting defense acquisition metrics, readiness reporting, and executive decision-support.
Current SECRET security clearance eligibility.

Responsibilities

Lead advanced data analytics, statistical modeling, data mining, and predictive decision-support activities for AMCOM SCMD.
Design, build, and deploy advanced analytical models to forecast supply demand, asset failure rates, repair turnaround times, and inventory requirements.
Develop interactive business intelligence dashboards, executive visualizations, and reporting tools using Power BI, Tableau, and custom analytics software.
Perform complex data extraction, cleaning, transformation, and validation across massive, disparate Army logistics and enterprise data sources.
Apply statistical techniques, regression analysis, machine learning algorithms, and operations research methodologies to solve complex supply chain challenges.
Analyze supply chain cycle times, data processing bottlenecks, error rates, and system compliance IAW contract AQL standards (<3% error rate, >95% turnaround).
Collaborate with Senior Logistics Analysts to translate operational supply chain queries into mathematical models and data science solutions.
Evaluate supply chain risk factors, readiness impacts, and mitigation strategies using predictive data simulation.
Automate recurring data extraction, reporting processes, and performance metric tracking to enhance analytical efficiency.
Develop technical documentation, statistical reports, trend analysis products (CDRL A009), and briefing decks for military and civilian executives.
Provide technical direction, code review, mentorship, and guidance to junior program/data analysts.
Ensure data handling complies with DoD cybersecurity directives, CUI protocols, AR 25-2, and Army information assurance standards.
Coordinate with internal software developers to integrate analytical algorithms into custom web applications and decision-support tools.
Participate in technical working groups, Army AI/ML initiatives, and enterprise data architecture discussions.