Senior Staff Engineer - Data Scientist at Jobgether – United States

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Staff Engineer - Data Scientist in the United States.

This role offers a unique opportunity to lead advanced data science initiatives in the manufacturing domain, driving measurable improvements across production, operations, and supply chain processes. You will work on end-to-end data solutions, from integrating industrial systems and extracting real-time data to building predictive models and delivering actionable insights. The position blends hands-on engineering with strategic problem solving, allowing you to influence operational efficiency and decision-making at scale. Ideal candidates are skilled in cloud-based data pipelines, machine learning, and industrial protocols, and can communicate complex analyses effectively to both technical teams and executive stakeholders. You will collaborate across remote, global teams in a dynamic, innovative environment that values impact, learning, and cross-functional expertise.

• Lead the development and deployment of predictive models for maintenance, anomaly detection, demand forecasting, and process optimization in manufacturing settings
• Build and optimize scalable cloud data pipelines for high-volume IoT and operational data using tools like Spark, Kafka, Airflow, and Delta Lake
• Integrate OT and IT systems including MES, SCADA, and ERP for real-time data extraction and analysis using industrial protocols such as OPC-UA, MQTT, and Modbus
• Apply statistical methods, Six Sigma, SPC, OEE, and lean methodologies to drive measurable gains in yield, uptime, and efficiency
• Translate complex model outputs into actionable insights and recommendations for operations and executive stakeholders
• Design and execute experiments and simulations to validate process improvements and quantify business impact
• Collaborate with cross-functional teams to ensure solutions align with business objectives and operational realities

• 8–10 years of overall data science experience with 2–4 years in the manufacturing domain
• Strong proficiency in SQL and Python, with hands-on experience in medallion/lakehouse architectures on platforms like Databricks, Snowflake, AWS, or Azure
• Proven experience in building, deploying, and operationalizing ML models in industrial environments using scikit-learn, TensorFlow, or PyTorch
• Deep understanding of industrial operations, production planning, and systems (MES, SCADA, ERP)
• Expertise in data engineering, cloud data pipelines, and IoT data integration
• Solid grounding in statistical methods: time series analysis, regression, clustering, hypothesis testing
• Strong communication skills with the ability to convey technical insights to non-technical stakeholders
• Experience designing A/B experiments and process simulations to evaluate business impact
• Adaptable, collaborative, and capable of working in a fast-paced, remote, and cross-functional environment

• Opportunity to work on cutting-edge data science projects in manufacturing and industrial operations
• Remote work with occasional travel across the United States
• Exposure to high-impact, enterprise-scale industrial data environments
• Collaborative, innovative, and non-hierarchical work culture
• Professional growth opportunities through hands-on experience with advanced ML and data engineering
• Competitive contract-to-hire compensation