Data Scientist (Supply Chain Risk Management (SCRM)) - Clearance Required

Key Skills

Data science techniques, Data Visualization, Effective communication skills, Natural Language Processing (NLP), Python Programming, SQL, Supply Chain Management, Tableau

Job Description

LMI is seeking a Supply Chain Risk Management (SCRM) Data Scientist to join our team. As a Supply Chain Risk Management (SCRM) Data Scientist, you will play a vital role in supporting our Health and Human Services Supply Chain Risk Management (SCRM) efforts. Your responsibilities will include initiating, integrating, managing, assessing, and providing focused analysis to enhance our SCRM operations. You will collaborate with Centers for Medicare & Medicaid Services (CMS) leadership, program personnel, and other government agencies to ensure the mission and objectives of CMS are met. Position is a hybrid work environment with a mix of telework and in person work in the Baltimore, MD region. 

Responsibilities

• Conduct end-to-end supply chain risk assessments to identify vulnerabilities, threats, and potential risks and deliver comprehensive reports and presentations on SCRM findings and recommendations to stakeholders and senior leadership. 
• Utilize analytical tools and techniques to gather, analyze, and interpret data for risk analysis and reporting. 
• Collaborate with cross-functional teams to identify process improvements and streamline supply chain workflows. 
• Implement data ingestion pipelines to collect and consolidate data from diverse sources using tools and external APIs for comprehensive supply chain risk assessment. 
• Apply statistical, machine learning, and natural language processing (NLP) algorithms to analyze large volumes of data, identify patterns, and uncover potential vulnerabilities and threats within the supply chain. 
• Utilize data visualization tools to create interactive dashboards and reports that provide actionable insights on supply chain risks and mitigation strategies. 
• Implement data quality and cleansing processes to ensure accuracy and reliability of supply chain data used in risk analysis. 
• Continuously evaluate and adopt emerging data engineering and data science techniques to enhance supply chain risk management capabilities. 
• Conduct exploratory data analysis and feature engineering to uncover hidden insights and develop new risk indicators for proactive supply chain risk mitigation. 
• Foster relationships with external partners and agencies to enhance risk analysis and information sharing. 
• Stay updated on the latest advancements in data engineering, data science, and supply chain technologies through industry conferences, training, and research to drive innovation in SCRM. 

Qualifications

• Minimum of 3 years of experience leveraging data analytics or data science approaches. Application of that experience in the area of supply chain management, supply chain risk management (SCRM), intelligence, or related field is preferred. 
• Bachelor's degree in data science, mathematics, statistics, economics, computer science, engineering, or a related business or quantitative discipline.
• Understanding of basic supply chain concepts to help to align data engineering and data science techniques with specific supply chain risk challenges. 
• Proficient in Excel and analytical tools and languages (e.g., SQL, Python) for data manipulation, feature engineering, analysis, and reporting. 
• Experience using data visualization tools like Tableau or Power BI to create interactive dashboards and reports for visualizing supply chain risks. 
• Excellent communication skills, with the ability to convey technical findings and insights to both technical and non-technical stakeholders. 
• Strong analytical thinking and problem-solving skills. 
• Continuous learning mindset and a passion for exploring new techniques to enhance SCRM capabilities. 
• Familiarity with SCRM tools and SCRM regulations and frameworks preferred. 
• Ability to obtain a security clearance. Active Secret clearance or Top Secret preferred.