Manufacturing Data Scientist - Blades & Vanes (HYBRID)
Siemens Energy
A Snapshot of Your Day As a Manufacturing Data Scientist - Blades & Vanes, you will transform complex manufacturing, inspection and IoT data into actionable insights that drive quality, efficiency, and innovation in our turbine components production. You will work closely with engineering, operations and quality teams, building advanced analytics models and automation solutions that enable data-driven decision-making across the blades and vanes value chain. Your work will support process optimization, defect reduction and yield improvement - making a direct impact on our manufacturing excellence. How You'll Make an Impact
Rewards/Benefits
#gernperDu Equal Employment Opportunity Statement Siemens Energy and Siemens Gamesa Renewable Energy is an Equal Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law. California Privacy Notice
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- Collection, consolidation, and integration of data from SAP, MES, PLM, inspection systems, and IoT sensors
- Ensuring data integrity, consistency, and compliance with Siemens Energy governance standards
- Development and maintenance of structured datasets and analytical models for production use cases, including process capability studies and statistical quality control
- Application of advanced data science methods for trend identification, anomaly detection, and root cause analysis to support continuous quality improvement
- Design and deployment of analytics solutions using Python, R, and BI tools (Power BI, Tableau), including automated reporting and realtime dashboards
- Collaboration with engineering and operations teams for the implementation of datadriven solutions and the translation of insights into process improvement and cost optimization
- Degree in Data Science, Statistics, Engineering, or a related technical discipline
- Several years of handson experience in advanced analytics within a manufacturing environment
- Proven experience in statistical analysis methods and tools (Python, R, SAS) and BI platform expertise (Tableau, Power BI, Alteryx)
- Familiarity with SAP data structures and manufacturing IT systems
- Understanding of blades and vanes manufacturing processes, including quality control and inspection workflows
- Ability to work effectively in Agile, crossfunctional teams and clear communication with technical and business stakeholders.
Rewards/Benefits
- Career growth and development opportunities
- Supportive work culture
- Company paid Health and wellness benefits
- Paid Time Off and paid holidays
- 401K savings plan with company match
- Family building benefits
- Parental leave
#gernperDu Equal Employment Opportunity Statement Siemens Energy and Siemens Gamesa Renewable Energy is an Equal Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law. California Privacy Notice
California residents have the right to receive additional notices about their personal information. Click here to read more .
Vacancy posted 9 hours ago
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