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# Data Scientist

- **Company:** nLIGHT Inc
- **Location:** United States
- **Experience:** Experienced
- **Salary:** $93,600.0 - $120,640.0
- **Contract:** Temporary contract
- **Skills:** Microsoft Excel, Application Programming Interfaces (APIs), Business Analytics Applications, Data Analysis, Big Data, Spreadsheets, Cloud Computing, Databases, Data Transformation, Relational Databases, Database Queries, Python (Programming Language), Machine Learning, Microsoft SQL Server, SQL Azure, Power BI, Standard Sql, Systems Integration, Information Technology
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/temporary-data-engineer-nlight-8005253

## About the Role

+ Strong SQL and relational database skills, including experience writing complex queries and working with Microsoft SQL Server and/or Azure SQL.
 + Experience integrating and transforming data from multiple sources, including on-premises and cloud-based systems.
 + Strong background in statistics, data analysis, and correlation methods, with proficiency in Python, R, or similar analytical tools.
 + Knowledge of semiconductor, laser, or other advanced manufacturing processes is preferred.
 + Demonstrated ability to work independently, manage complex data challenges, and communicate findings effectively to a range of audiences.
 + Advanced Excel skills are required; experience with Power BI is preferred.
 + Experience working with complex enterprise data environments and large datasets.
 + 3+ years of hands-on data analysis experience in a high-tech manufacturing, semiconductor, or similar environment is preferred.
 + Master's degree or Ph.D. in Data Science, Statistics, Computer Science, Engineering, or a related field is preferred.
 + Lean, Six Sigma Green Belt, or Black Belt certification is a plus.

## Description

+ Collect, clean, and structure data from multiple sources, including databases, APIs, and spreadsheets, to support meaningful analysis.
 + Develop, test, and apply statistical models, analytical methods, and machine learning techniques to solve business and manufacturing challenges.
 + Create reports, dashboards, and visualizations that translate technical findings into clear insights for non-technical audiences.
 + Partner with cross-functional teams, including Operations and Planning, to identify opportunities for improved performance and decision-making.
 + Present findings and recommendations to internal stakeholders in a clear, concise, and actionable manner.


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