Sr Data Analyst- Supply Chain Management

Sierra Space•Louisville, CO

About The Position

The Lead Supply Chain Data Scientist will drive advanced analytics and data science initiatives to optimize supply chain operations, with a focus on Materials Requirements Planning (MRP) system accuracy, inventory optimization, and production scheduling. This role combines deep supply chain domain expertise with advanced statistical modeling, machine learning, and AI capabilities to transform complex datasets into actionable business insights. The position requires both technical excellence in data science and strategic leadership in supply chain analytics.

Requirements

Bachelor's degree in Supply Chain Management, Business Analytics, Data Science, Operations, Engineering, Statistics, Computer Science, or a related field (or equivalent work experience in lieu of degree; Masters degree with 6+ years of experience also qualifies)
Typically 8+ years of progressive experience combining: Material planning, production planning, or supply chain analytics
Data science, statistical modeling, and machine learning applications
Focus on system optimization and process improvement
Strong experience with SAP MRP and advanced data visualization tools (Power BI or similar tools)
Advanced Excel skills (modeling, VBA) and SQL knowledge to extract and manage data
Expertise in programming languages such as Python, R, and SQL
Comprehensive understanding of IT systems, software development data, CI/CD, and business processes
Strong understanding of database environments and upgrades

Nice To Haves

Advanced degree (Masters or PhD) in Data Science, Statistics, Operations Research, Industrial Engineering, Supply Chain Management, or related field
Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn
Strong knowledge of statistical analysis and data mining techniques
Experience with big data technologies such as Hadoop, Spark, and Kafka
Familiarity with data visualization tools such as Power BI, Tableau, or Looker
Experience with cloud-based data platforms such as AWS, Azure, or Google Cloud
Strong understanding of CI/CD pipelines and tools such as Jenkins, GitLab CI, or CircleCI
Experience with version control systems like Git
Experience with MLOps platforms and model deployment best practices
APICS CPIM (Certified in Production and Inventory Management) or CSCP (Certified Supply Chain Professional) certification is highly desirable
Proven track record of leading analytics initiatives and driving measurable business impact
Experience in supervising, mentoring, and coaching other analysts and data scientists
Deep understanding of supply chain operations, inventory management, and production planning principles
Experience with Sales, Inventory, and Operations Planning (SIOP) processes

Responsibilities

Develop and execute analytics strategies aligned with business and supply chain objectives, translating complex data into actionable insights
Apply advanced statistical and machine learning techniques to analyze complex supply chain datasets
Develop and scale Generative AI and Agentic AI capabilities, including copilot, RAG, and workflow automation solutions for supply chain applications
Drive technical strategy, best practices, AI governance, and adoption of enterprise AI capabilities
Generate actionable insights from data analysis to support strategic business decisions
Provide data insight to support and improve processes to enhance service quality, efficiency, and customer satisfaction
Develop, manage, and maintain key supply chain performance and financial metrics, including on-time delivery, supplier quality, Purchase Order projections, Goods Receipt projections, Purchase Price Variance trend, and Excess & Obsolescence trend
Develop and maintain a Supply Chain Metrics platform for use by leadership at multiple levels of the organization
Support the Sales, Inventory, and Operations Planning (SIOP) process by compiling, analyzing, and presenting supply chain data to cross-functional stakeholders
Monitor and report on inventory levels, identifying trends, risks, and opportunities for optimization
Utilize AI/BI tools to analyze MRP outputs (planned orders, exception messages) and perform what-if simulations to forecast material shortages or excesses
Configure, maintain, and optimize MRP parameters (e.g., safety stock, lot sizes, lead times, safety time) within the ERP system (SAP) to maximize service levels while minimizing inventory investment
Own the accuracy, performance, and optimization of the Materials Requirements Planning system
Analyze large datasets to identify bottlenecks in replenishment and production scheduling
Ensure data accuracy, completeness, and consistency across supply chain systems and reporting platforms
Comprehensive understanding of IT systems, software development data, CI/CD, engineering, and business processes
Strong understanding of database environments and upgrades
Utilize SQL, Python, R, PowerBI, and other analytics/data platforms to manipulate large datasets, perform root cause analysis, and automate reporting
Partner with supply chain, manufacturing, procurement, quality, and engineering teams to solve complex business problems
Serve as the primary liaison between Procurement, Production, Business Development, and IT to align MRP strategies with customer demand and capacity planning
Collaborate with engineering teams to operationalize solutions using modern cloud and MLOps platforms
Identify opportunities for automation, system integration, and process optimization to improve MRP efficiency and decision-making speed
Identify areas for improvement, develop improvement plans, and lead implementation thereof
Proven track record of process improvement and implementation
Mentor, coach, and manage a team of analysts, data scientists, or planners
Provide thought leadership across analytics and AI initiatives
May supervise, mentor, and/or coach other business systems analysts