About the Role:
We are looking for a Data Scientist with 23 years of experience to join our growing Industrial AI team. This role is ideal for someone who has worked on data science projects in the manufacturing, oil & gas, or utilities sectorparticularly around asset reliability, predictive maintenance, and failure prediction. Exposure to Gen AI applications (e.g., document intelligence, knowledge retrieval) is highly desirable.
You will be responsible for developing and deploying ML/AI solutions that drive operational excellence, reduce unplanned downtime, and improve decision-making using both structured and unstructured data.
Key Responsibilities:
- Develop predictive models to forecast equipment failures, optimize maintenance cycles, and improve asset reliability.
- Work on time-series sensor data and apply statistical and machine learning techniques for anomaly detection and condition monitoring.
- Build and deploy Generative AI solutions using open-source and proprietary LLMs to automate insights generation from industrial documents, manuals, and maintenance logs.
- Collaborate with domain experts, data engineers, and MLOps teams to ensure successful deployment and scaling of AI solutions.
- Evaluate and fine-tune ML models using real-world production data.
- Interpret and communicate model results clearly to non-technical stakeholders.
Preferred Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field.
- 23 years of hands-on experience in industrial data science or reliability engineering analytics.
- Strong programming skills in Python and familiarity with ML libraries like scikit-learn, XGBoost, PyTorch/TensorFlow.
- Experience with time-series analysis, anomaly detection, and survival models.
- Familiarity with Generative AI concepts and experience using models like GPT, Llama, or Qwen for industrial use cases.
- Experience with cloud platforms (GCP, AWS, Azure) is a plus.
- Knowledge of manufacturing/O&G plant data like sensor logs, DCS/SCADA systems, CMMS, etc. is a strong plus.
Nice to Have:
- Experience working with industrial IoT data pipelines.
- Exposure to visualization tools like Power BI or Plotly Dash for operational dashboards.
- Prior involvement in AI POCs or production deployments for industrial clients.
