R&D Machine Analytics

As a family-run, high-tech company with nearly 19,000 employees at 71 locations worldwide, we are looking for forward thinkers with unconventional ideas and drive to join our team. Our company culture, which values collaboration and mutual trust, creates the ideal framework for boldly trying new things and questioning the status quo. Our technologies inspire people to develop and produce things that are currently unimaginable. Whether lasers, machine tools, EUV or electronics - TRUMPF is building technological worlds for future generations. Are you ready for new challenges?

The SCC Machine Analytics team transforms large-scale machine status, sensor, and process data into practical tools that help TRUMPF technical service and engineering teams understand machine conditions, diagnose issues, and make faster, more confident decisions. As a R&D Machine Analysist, you will combine software engineering, data analytics, statistical modeling, and machine-learning expertise to develop reliable data-driven products for machine monitoring and technical support. You will build and maintain internal web applications, dashboards, APIs, and data pipelines while developing and validating algorithms for condition assessment, anomaly detection, issue identification, failure diagnosis, and forecasting. This role requires close collaboration with technical service, machine R&D, testing, and other business partners to translate real-world diagnostic challenges into dependable analytical solutions.

Duties & Responsibilities

• Develop and maintain internal web applications, dashboards, APIs, data pipelines, and analytics tools supporting technical service and engineering operations.
• Analyze machine, sensor, process, and operational data to diagnose complex issues, identify patterns and root causes, and support machine monitoring.
• Develop, validate, and maintain statistical, predictive, and machine-learning models for condition assessment, anomaly detection, failure diagnosis and prediction, time-series analysis, and forecasting.
• Apply advanced statistical, mathematical, and analytical methods to derive actionable insights from structured and unstructured data.

• Design and implement efficient Python solutions while working with relational databases and T-SQL to deliver robust ETL pipelines, seamless data integration, optimized query performance, and high-quality data management.

• Apply software-engineering and DevOps practices for testing, version control, deployment, monitoring, containerization, and maintenance.
• Collaborate with technical service, R&D, testing, product specialists, and other stakeholders to translate diagnostic challenges into practical data-driven solutions.
• Integrate analytical results into user-friendly tools that improve troubleshooting and decision-making.

• Translate complex analytical findings and model performance metrics into clear, actionable recommendations for technical and non-technical stakeholders.

• Proactively identify and resolve data, analytical, and implementation risks; work independently, perform additional duties as needed, and comply with applicable safety requirements.

Experience & Education

• 3+ years of experience developing data-intensive applications, analytics solutions, data pipelines, or related technical solutions.
• Strong Python and SQL/T-SQL skills, with experience in relational databases, ETL, data integration, optimization, data quality, and large or multi-source datasets.
• Experience applying statistical analysis, machine learning, predictive modeling, anomaly detection, time-series analysis, forecasting, and data visualization.
• Experience developing web-based, cloud, and containerized applications using technologies such as Flask, FastAPI, React, Azure, PySpark, or Databricks, with knowledge of DevOps and CI/CD practices.
• Experience with industrial IoT data, predictive analytics, and/or business-intelligence tools such as Power BI or Tableau.
• Experience applying generative AI/LLMs to software development, data analysis, technical support, or business applications.
• Strong analytical, problem-solving, communication, and collaboration skills, with the ability to translate complex technical concepts into practical solutions and work independently.
• Knowledge of TRUMPF products, machine tools, laser technology, or industrial manufacturing, and German language skills, are a plus
• Bachelor’s degree or equivalent work experience in Computer Science, Computer Engineering, Data Science, Data Engineering, Mathematics, Statistics, Business Analytics, Economics, Physics, Engineering, or a related discipline.
• A master’s degree in a related technical field is preferred.

Pay & Benefits

• Retirement: 401(k) with generous company match 

• Health & Wellness: Comprehensive medical, dental, and vision benefits with employer HSA contributions and 100% employer-paid vision premiums for employees and eligible dependents.

• Education Assistance: Tuition reimbursement and student loan guidance to support your continued learning 

• Family Support: Paid family and parental leave programs, plus comprehensive reproductive and family health resources 

• Work-Life Balance: Paid time off available from day one, plus 11 paid company holidays 

• Income Protection: Company-paid life insurance at two times base salary, along with short- and long-term disability coverage 

• Additional Programs: Gym membership subsidy, employee referral bonuses, recognition awards, and a scholarship program for employees' children

Pay Range: $80,686 - $138,450

TRUMPF Inc. endeavors to make TRUMPF careers pages accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance in completing the applications process, please contact our HR department at 860.255.6000 or at HRgeneral@us.trumpf.com. This contact information is for accommodation requests only and can not be used to inquire about the status of application.

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law.