Senior Data Analyst Supply Chain

Topsarge Business Solutions, LLC; Alabama; On-site; USD 90,000 - 140,000; Full time

Job summary

Topsarge Business Solutions, LLC seeks an experienced analytics leader to drive descriptive, predictive, and prescriptive insights across supply chain operations.

You will oversee data mining, forecasting, modeling, ML, visualization, reporting, and mentoring of junior analysts; translate findings into actionable recommendations for senior leadership and operational managers. Strong communication and an active security clearance or eligibility are required.

Qualifications

• Bachelor's in Logistics, Business, or related field.
• 7+ years analytics experience.
• 3+ years supply-chain analytics experience.
• Experience with statistical modeling, machine learning, Tableau or Power BI, data mining, forecasting, data quality, and reproducible analysis.
• Good communications skills.
• SECRET clearance or eligibility.

Responsibilities

• Distribute structured surveys to end users and stakeholders for feedback on service quality, responsiveness, and overall satisfaction.
• Conduct interviews to obtain qualitative feedback and identify areas for improvement.
• Track and analyze KPIs, monitor customer complaints, service tickets, and issue logs.
• Hold regular review meetings to discuss performance and gather feedback.
• Conduct after-action reviews following major projects or deliveries to assess satisfaction and identify lessons learned.

Skills

Statistical modeling

Machine learning

Data mining

Tableau / Power BI

Forecasting

Data quality

Communication

Reproducible analysis

Education

Bachelor's in Logistics, Business, or related field

Tools

Tableau

Power BI

Job description

Leads descriptive, predictive, and prescriptive analytics supporting supply availability, performance management, and decision-making. Oversees data mining, cleansing, statistical analysis, forecasting, modeling, machine learning, visualization, reporting, and mentoring of junior analysts; presents findings to stakeholders. Collects, processes, and analyzes data to extract meaningful insights, identify patterns, and support decision-making utilizing tools and technologies such as data mining, Artificial Intelligence (AI), machine learning, and data visualization. Transforms raw data into actionable information. Prepares reports, correspondence, and other written materials making recommendations on organizational matters affecting program support. Integrates multiple disciplines within an operations research team, translating analytical methods into practical applications for operational managers. Implements quality control methods, collects and analyzes data for key enterprise metrics (such as Material Requirements Planning (MRP) adherence, forecast accuracy, supply availability, and excess inventory), and prepares and updates processes to support the use of analytic tools, procedures, and methodologies. Distills both structured and unstructured data into cohesive analytical products for functional business areas, supports pattern analysis to develop recommendations for operational managers, and prepares reports and briefings to communicate courses of action to senior leadership. Data analytics may include descriptive analytics, Diagnostic analytics, Predictive analytics, and Prescriptive analytics. Monitor and analyzes supply, demand, receipt, and issue activities. Monitors customer satisfaction and prepares and submits customer satisfaction reports. Selects and implements appropriate methods such as

• Distributing structured surveys to end users and stakeholders for feedback on service quality, responsiveness, and overall satisfaction
• Conducting interviews to obtain qualitative feedback and identify areas for improvement
• Tracking and analyzing KPIs,
• Monitoring and analyzing customer complaints, service tickets, and issue logs,
• holding regular review meetings to discuss performance and gather feedback,
• conducting after-action reviews following major projects or deliveries to assess satisfaction and identify lessons learned

Requirements

• Bachelor's in Logistics, Business, or related field
• 7+ years analytics
• 3+ years supply-chain analytics
• Experience with statistical modeling; machine learning; Tableau or Power BI; data mining; forecasting; data quality; and reproducible analysis
• Good communications skills
• SECRET clearance or eligibility