Data Analyst

Kaman•Middletown, CT

About The Position

Precision Fusing and Sensors is hiring a Data Analyst for its Operations Department in Middletown, Connecticut. The role supports the collection, integration, analysis, and visualization of business performance data across departments. The analyst will work with disparate and sometimes inconsistent data sources to build practical reporting solutions and dashboards that help leaders make informed decisions, without relying on an established reporting infrastructure. The position uses modern technologies, including AI, automation, and advanced analytics, to improve reporting, visualize trends, monitor performance, and identify opportunities for improvement. The analyst partners with manufacturing engineering, quality assurance, and shop-floor teams to connect data insights with Lean-Six Sigma and continuous improvement goals, and helps build a data-driven culture across the organization. The work includes integrating and managing data from legacy systems and other sources; developing reliable data models and automated collection processes; designing and maintaining interactive dashboards and reports; creating and improving analytical tools; documenting data sources, reporting logic, KPIs, and processes; and training and supporting business users.

Requirements

Bachelor's or master's degree in Data Analytics, Data Science, Computer Science, Information Systems, Mathematics, or Statistics from an accredited institution.
At least 3 years of data analytics experience.
Demonstrated experience integrating data from multiple systems and working with complex or inconsistent datasets.
Understanding of Lean manufacturing principles, 5S, Gemba, root-cause analysis, and statistical process control (SPC).
Strong desire to work in an advanced manufacturing environment.
Excellent written and oral communication skills.
Ability to work in a self-directed and cross-functional team environment.
Strong organizational skills and attention to detail.
Working knowledge of statistical analysis.
Experience with SAS, Minitab, JMP, MS Excel, M-Code, or Six-Sigma.
Experience with Microsoft 365, including Power Automate and Power Apps.
Experience using Power BI or another tool demonstrating value-added applications.
Experience using SQL and Python.
Knowledge of Lean manufacturing.
Strong analytical and problem-solving abilities.

Nice To Haves

Previous experience in a manufacturing environment.
Experience with legacy ERP, manufacturing, quality, financial, or operational management systems.
Proficiency in Python, Power Automate, or other scripting and automation tools.
Experience with Microsoft Fabric, Azure, cloud-based data platforms, or comparable technologies.
Practical experience using generative AI tools, AI-assisted coding, or machine learning applications to support data analysis.
Experience developing automated anomaly detection, exception reporting, or predictive analytics.
Understanding of manufacturing or operational KPIs, including productivity, quality, delivery, inventory, cost, and financial performance.
Experience developing reporting environments from the ground up or modernizing existing reporting processes.

Responsibilities

Use AI, automation, and advanced analytics to improve reporting, visualize trends, monitor business performance, and highlight opportunities for improvement.
Partner with manufacturing engineering, quality assurance, and shop-floor teams to align data insights with Lean-Six Sigma and continuous improvement goals.
Connect information with company functions and help establish standardized systems for gathering, understanding, and sharing data.
Promote a data-driven culture through interactions with employees at multiple organizational levels, from engineering leaders to production operators.
Extract, consolidate, and organize data from legacy business systems, databases, spreadsheets, and other information sources.
Develop repeatable processes for sorting, validating, transforming, and standardizing data.
Build and maintain reliable data models that connect information across business functions and systems and make them accessible to stakeholders.
Identify and resolve data quality issues, inconsistencies, and gaps.
Develop automated data collection processes to reduce manual reporting.
Design, develop, and maintain interactive dashboards and reporting solutions that make complex data clear and actionable.
Create visual presentations of KPIs, trends, and operational results.
Develop reporting tools that let users drill down from executive summaries into transactional and operational details.
Continuously improve the effectiveness, usability, and accessibility of reporting.
Independently develop reports and analytical tools in response to evolving business needs.
Select and deploy technologies to support reporting and make data easier to gather and report.
Collaborate with stakeholders to understand business problems and develop solutions.
Document data sources, reporting logic, KPI definitions, and processes as data systems change.
Train and support business users in using dashboards and reporting tools.