Senior Data Scientist

Role Overview

• Be a part of the design, development, and deployment of advanced AI/ML models for predictive maintenance, process optimization, and industrial performance intelligence.
• Collaborate closely with Product, Engineering, and Customer Success teams to translate business problems from industrial domains into data science solutions.
• Guide the team in handling complex, high-dimensional, and time-series sensor data from IoT, SCADA, and DCS systems.
• Drive model interpretability, scalability, and accuracy, ensuring robust performance in real-world production environments.
• Hybrid Modeling: Integrate First-Principles Models (mass/energy balances, kinetics) with data-driven ML to ensure physical consistency in model outputs.
• Signal Processing: Lead the strategy for feature engineering on high-frequency telemetry data from SCADA/DCS, focusing on transient state detection and steady-state identification.
• Operationalization: Move beyond "notebook AI" to deploy robust, low-latency inference pipelines that respect the edge-computing constraints of industrial environments.
• Partner with industry experts and customers to validate models, derive insights, and deliver measurable business outcomes.
• Stay ahead of emerging trends in AI/ML, deep learning, and industrial AI to incorporate innovative techniques into UptimeAi’s product roadmap.
• Contribute to thought leadership by publishing whitepapers, patents, or presenting at industry conferences.
• Mentor and provide technical leadership to data scientists, ensuring continuous upskilling and adoption of best practices.

Requirements

• Bachelor’s or higher in Chemical Engineering, Mechanical Engineering, Aerospace, or Applied Physics with a heavy emphasis on computational modeling. (Candidates with CS degrees are welcome if they have significant experience in heavy industry).
• 5+ years of hands-on experience developing and deploying ML models specifically within Manufacturing, Energy, Oil & Gas, or Power sectors.
• Strong background in handling time-series and sensor data from industrial or IoT systems.
• Hands-on experience with Python, TensorFlow/PyTorch, Scikit-learn, SQL, and cloud ML platforms (AWS, Azure, GCP).
• Excellent problem-solving and communication skills with the ability to influence senior stakeholders.
• Demonstrated ability to lead and mentor teams while being a hands-on contributor
• Ability to work independently, with strong problem-solving and decision-making abilities.

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• IoT
• Python
• PyTorch
• Scikit-Learn
• SQL
• Tensorflow

Benefits

• Impact Industry-Wide Change: Contribute to transformative solutions that significantly improve operational efficiency and reliability for global clients.
• Collaborative and Growth-Oriented Environment: Join a talented, passionate team that values innovation, continuous learning, and professional growth.
• Opportunities for Leadership and Innovation: Lead pioneering projects, influence product development, and shape the future of industrial AI solutions.