As a Data Scientist in our factory-based team, you'll design and deploy machine learning solutions that keep production lines running smarter, faster, and more efficiently. You’ll work side-by-side with engineers, production teams, and quality team to turn raw factory data into predictive insights and real-time decisions.
Responsibilities
Collaborate with process and production engineers to identify data-driven improvement opportunities.
Design automated data pipelines using Python (Pandas, Scikit-learn, etc.) to transform messy factory data into usable datasets.
Develop real-time dashboards and reports using Power BI, Tableau, or web-based visualization tools.
Integrate models with factory systems via API, working closely with software and automation teams.
Apply statistical analysis (e.g., hypothesis testing, time-series analysis, control limits) to uncover anomalies or trends in equipment and process performance.
Translate complex data findings into clear, actionable recommendations for engineering and production teams.
Qualifications
Bachelor’s degree in Computer Engineering, Data Science, Digital Engineering or related.
0–3 years of experience in data science (Internships and co-op experiences are welcome)
Solid Python skills with experience in pandas, scikit-learn, or similar ML libraries.
Experience with SQL and working with relational databases.
Familiar with data visualization tools (Power BI, Tableau, or frontend tools like JS/Plotly).
Basic understanding of manufacturing processes, production KPIs, or quality control logic.
Clear communication skills – you can explain data and model insights to non-technical teammates.
Bonus If You Have
Experience working with production data in a factory or electronics manufacturing environment.
Knowledge of cleanroom data, SPC, OEE, yield monitoring, or machine log files.
Experience building and deploying API-based solutions or dashboards.
Familiarity with SharePoint, Power Apps, Power Automate, or other low-code tools.
Work Setup
100% Onsite at our production plant — this role is hands-on and close to real machines, real operators, and real decisions.
Occasionally requires access to cleanroom areas (we provide gear).
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