Lead Data Analyst – Supply Chain Analytics (Secret)

PingWind, Inc.; Huntsville (AL); On-site; USD 99,000 - 138,000; Full time

Benefits offered by this job

Medical Insurance

401k with match

Paid Time Off

Parental Leave

Education assistance

Job summary

PingWind is seeking a Senior Data Analyst to lead advanced data analytics, statistical modeling, and BI initiatives supporting government and logistics operations. You will guide data-driven decisions by transforming complex data into actionable insights and mentoring junior analysts.

The role emphasizes developing descriptive and predictive analytical products, performance dashboards, and KPIs, with oversight of data quality and analytical best practices across projects.

Qualifications

• Bachelor's degree in a quantitative field.
• Seven years of professional data analytics experience.
• Three years in analytics for supply chain/logistics or related operations.

Responsibilities

• Serve as technical lead for data analytics, statistical analysis, and predictive modeling.
• Develop descriptive, diagnostic, and predictive analytical products for supply chain and logistics.
• Analyze large datasets to identify trends, risks, and opportunities for operational improvement.
• Develop and apply statistical and predictive models to support forecasting and decision making.
• Create dashboards and dashboards using Tableau or Power BI to monitor KPIs.
• Translate analytic findings into actionable recommendations for government stakeholders.

Skills

Data analytics

Statistical analysis

Data mining

Machine learning

Predictive modeling

SQL

Data visualization

Education

Bachelor's degree in Data Science or related field

Tools

Tableau

Power BI

Python

R

Job description

PingWind is seeking a Senior Data Analyst to lead advanced data analytics, statistical modeling, and BI initiatives supporting government and logistics operations. You will guide data-driven decisions by transforming complex data into actionable insights and mentoring junior analysts.

The role emphasizes developing descriptive and predictive analytical products, performance dashboards, and KPIs, with oversight of data quality and analytical best practices across projects.