Senior Data Scientist

UptimeAI is leading the way in predictive analytics and AI-driven solutions to optimize operational uptime and reduce downtime for industrial and enterprise clients. Our innovative platform harnesses cutting-edge data science to deliver actionable insights, ensuring maximum efficiency and reliability. UptimeAI uniquely combines Artificial Intelligence with Subject Matter Knowledge from 200+ years of cumulative experience to explain interrelations across upstream/downstream equipment, adapt to changes, identify problems, and give prescriptive diagnosis like a human expert would.

Recently receiving a funding round led by WestBridge Capital, UptimeAI is prime for global expansion

Role : Lead / Principal Data Scientist

Location: Bangalore- Karnataka (Hybrid)

Experience: 5+ years

Department: Data Science

Role Overview

We are looking for individuals who sit at the intersection of Data Science and Physical Sciences. You understand that industrial data isn't just rows in a database—it represents thermodynamics, fluid dynamics, and mechanical stress. The candidate should be capable of translating business problems into scalable AI solutions, leveraging creative thinking and first-principles problem solving.

This role requires someone who can:

· Build and deploy production-grade AI systems, not just prototypes

· Design agentic workflows that can reason, adapt, and take actions in dynamic environments

· Work with noisy, incomplete, and real-time industrial data to derive meaningful insights

· Collaborate closely with domain experts (e.g., operations, reliability, or plant engineers) to create context-aware AI solutions

· Demonstrate innovative thinking in solving ambiguous problems where standard approaches may not apply

· 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

· 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

· 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.