Minimum 6 years of experience as a Data Scientist.
Strong SQL and Python proficiency with experience in medallion/lakehouse architectures.
Proven track record building and deploying machine learning models focused on maintenance and forecasting.
Experience with industrial protocols (OPC-UA, MQTT, Modbus).
Hands-on experience in manufacturing operations and processes.
Responsibilities
Bridge OT and IT systems for real-time data extraction.
Build scalable cloud data pipelines leveraging Spark and Kafka.
Perform statistical analysis including time series and regression.
Design and conduct A/B experiments to validate process changes.
Communicate model outputs into actionable recommendations for stakeholders.
Benefits
Flexible remote work environment.
Opportunity for hands-on experience in advanced manufacturing environments.
Collaboration with cross-disciplinary teams to drive innovation.
Full Job Description
Job Description
Role: Data Scientist Location: Remote, USA Duration: Fulltime Employee
Job Overview:
Manufacturing 8-10 years in manufacturing (optional) with hands-on experience in shop floor operations, production planning, and systems including MES, SCADA, and ERP.
Proficient in industrial protocols (OPC-UA, MQTT, Modbus) with ability to bridge OT/IT systems for real-time data extraction.
Applied experience with OEE, Six Sigma, SPC, and lean methodologies to drive measurable gains in yield, uptime, and efficiency.
Data Engineering Skilled in building scalable cloud data pipelines for high-volume manufacturing and IoT data using Spark, Kafka, Airflow, and Delta Lake. Proficient in scikit-learn, TensorFlow, or PyTorch with experience moving models from prototype to production in industrial environments.
Strong communicator - able to translate complex model outputs into clear, actionable recommendations for operations and executive stakeholders.
Solid grounding in statistical methods - time series, regression, clustering, and hypothesis testing applied to manufacturing quality problems.
Experience designing A/B experiments and simulations to validate process changes and quantify business impact before full deployment.
Qualifications
Must Have:
Minimum 6 years of experience as Data Scientist.
Strong SQL and Python proficiency with hands-on experience in medallion/lakehouse architectures on Databricks, Snowflake, AWS, or Azure.
Data Science Proven track record building and deploying ML models for predictive maintenance, anomaly detection, demand forecasting, and root cause analysis.
