Data Scientist

Position Summary

We are seeking a Data Scientist (Contractor) to support our ongoing digital transformation initiatives. The contractor will be responsible for analyzing complex datasets, developing data pipeline strategies, and implementing AI/ML models to transition our operations from reactive to predictive. This role requires both technical expertise and business acumen to ensure data-driven insights lead to tangible process improvements.

Scope of Work / Key Responsibilities

• Design and implement data collection, storage, and archiving pipelines to support efficient access and analysis.
• Integrate data from multiple sources, including manufacturing equipment, MES, SAP, and other enterprise systems.
• Ensure both real-time and historical data are accurately captured and maintained.
• Perform exploratory and statistical analysis to identify patterns, correlations, and trends across business and manufacturing data.
• Build and deploy predictive and machine learning models to support proactive decision-making and process optimization.
• Collaborate with stakeholders to define KPIs and develop dashboards or reports for actionable insights.
• Analyze current business and operational processes to identify opportunities for automation and digital transformation.
• Design and implement data-driven workflows that streamline operations and enhance efficiency.
• Work closely with business process owners, IT, and operations teams to ensure alignment with strategic goals.
• Document methodologies, data architecture, and models to support sustainability and handover to internal teams.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Engineering, Computer Science, Statistics, or related field.
• 3+ years of professional experience in data science, analytics, or machine learning, preferably in a manufacturing or medical device environment.
• Proven experience developing and deploying data pipelines and predictive models.
• Proficiency in Python, SQL, and data visualization tools (e.g., Power BI, Tableau).
• Familiarity with data platforms (e.g., Azure, AWS, or GCP) and integration of enterprise systems such as MES and SAP.
• Strong understanding of industrial, IoT, or equipment-level data.
• Excellent communication and problem-solving skills.
• Ability to translate complex analytical concepts into actionable business strategies.
• Self-driven and capable of working independently within cross-functional teams.

Deliverables

• Data pipeline strategy and implementation plan.
• Predictive and analytical models for key business processes.
• Dashboards or visualization tools for ongoing data monitoring.
• Documentation of data architecture, models, and recommendations for long-term adoption.