Job Description
Role Overview
We are looking for a Senior Data Scientist to design, build, and deploy advanced machine learning models for industrial applications. The role will focus on transforming complex operational, sensor, production, and process data into reliable predictive and prescriptive solutions that improve efficiency, quality, safety, and decision-making.
The ideal candidate has strong experience in applied machine learning, statistical modeling, industrial data, and production-grade model development.
Key Responsibilities
Develop, validate, and deploy machine learning models for industrial use cases such as predictive maintenance, process optimization, anomaly detection, quality prediction, demand forecasting, and asset performance monitoring.
Work with large-scale structured and time-series data from industrial systems, sensors, machines, production lines, and operational platforms.
Collaborate with engineers, domain experts, product teams, and business stakeholders to identify high-value machine learning opportunities.
Translate industrial challenges into data science problems and deliver practical, scalable solutions.
Build robust data pipelines, feature engineering workflows, and model evaluation frameworks.
Monitor model performance in production and support continuous improvement of deployed models.
Communicate model insights, assumptions, limitations, and business impact clearly to technical and non-technical stakeholders.
Required Qualifications
Master’s or PhD in Data Science, Computer Science, Statistics, Mathematics or a related field.
Strong professional experience as a Data Scientist, Machine Learning Engineer, or similar role.
Proven experience building machine learning models for real-world, production-oriented use cases.
Strong knowledge of supervised and unsupervised learning, time-series modeling, anomaly detection, optimization, and statistical analysis.
Experience working with industrial, manufacturing, energy, logistics, process, or IoT data.
Proficiency in Python and common machine learning libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow, pandas, NumPy, or similar.
Experience with SQL and large-scale data processing.
Understanding of MLOps practices, model deployment, monitoring, versioning, and reproducibility.
Strong communication skills and ability to work across technical and business teams.
Preferred Qualifications
Experience with predictive maintenance, digital twins, process control, industrial automation, or sensor analytics.
Familiarity with cloud platforms such as Azure.
Experience with Databricks, Spark, Kubernetes, MLflow, Airflow, or similar tools.
Knowledge of edge deployment or real-time machine learning systems.
Desired Skills
Industrial machine learning
Time-series forecasting
Predictive maintenance
Anomaly detection
Feature engineering
Statistical modeling
MLOps
Python
SQL
Cloud platforms
Data pipelines
Model deployment and monitoring
What Success Looks Like
Success in this role means delivering machine learning models that are technically robust, operationally reliable, and valuable to industrial users. The Senior Data Scientist will help turn industrial data into measurable improvements in productivity, reliability, quality, and cost efficiency.
No Referrers Available
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