Sr. Data Scientist - Industrial Industry Focused in United States at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Sr. Data Scientist - Industrial Industry Focused in the United States.

This role offers the opportunity to build and deploy advanced machine learning solutions that transform industrial sensor and operational data into predictive insights that improve reliability, efficiency, and asset performance. You will work at the intersection of time-series analytics, AI, and industrial engineering to develop models for predictive maintenance, anomaly detection, and process optimization. The position involves close collaboration with engineering, product, and domain experts to turn complex operational challenges into scalable, production-grade data science solutions. You will have visibility into real-world impact as your work helps reduce downtime and improve critical industrial operations across sectors such as manufacturing, energy, and aerospace. The environment is highly technical, research-informed, and focused on building robust, end-to-end ML systems. This role is ideal for a data scientist who thrives in applied, high-impact industrial AI settings.

In this role, you will be responsible for designing and deploying advanced machine learning systems that process industrial sensor data and enable predictive, scalable, and production-ready analytics solutions.

• Develop, train, and deploy machine learning models for time-series, sensor, and industrial IoT data
• Build predictive maintenance, anomaly detection, and forecasting models using statistical and deep learning techniques
• Perform data preprocessing, feature engineering, and signal processing on large-scale, noisy industrial datasets
• Design and maintain end-to-end ML pipelines, including data ingestion, model training, deployment, and monitoring
• Apply statistical analysis, experimentation, and validation techniques to ensure model robustness and reliability
• Collaborate with engineering and domain experts to translate operational challenges into data science solutions
• Communicate insights, model results, and business impact to technical and non-technical stakeholders

This position requires strong expertise in applied machine learning, industrial data systems, and production-grade model development in complex, real-world environments.

• Bachelor’s degree in Engineering (Mechanical, Electrical, Chemical, Aerospace preferred) or related field
• 5+ years of experience in data science, machine learning, signal processing, or applied analytics
• Proven experience working with time-series, sensor, or industrial IoT data in production environments
• Strong proficiency in Python (NumPy, pandas, scikit-learn, TensorFlow/PyTorch), SQL, and visualization tools
• Experience building and deploying ML models for predictive maintenance, anomaly detection, or asset monitoring
• Familiarity with MLOps practices including CI/CD, model versioning, and pipeline orchestration tools
• Strong analytical thinking and ability to solve complex engineering-driven data problems
• Excellent communication skills and ability to collaborate across technical and business teams

• Competitive salary ranging from $98,837 to $154,546 depending on experience
• Fully remote position within the United States (excluding certain states)
• Health, dental, and vision insurance coverage
• 401(k) plan with employer contributions
• Paid time off and paid holidays
• Life, disability, and additional insurance coverage options
• Opportunities to work on high-impact industrial AI applications
• Exposure to advanced machine learning research and real-world deployments in critical industries