Data Scientist

About UptimeAI:

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 : Data Scientist - Agentic AI, Full-Stack Engineering

Location: Bangalore- Karnataka (Hybrid)

Experience: 3+ years

Department: Data Science

We are looking for a unique breed of Data Scientist who thrives at the intersection of Agentic AI, Full-Stack Engineering, and Industrial Design Thinking. Sitting within the Data Science team, you will be the bridge between algorithmic research and tangible product impact. You aren't just building models in a vacuum; you are leveraging modern AI-native development tools (Claude Code, Cursor, Antigravity) to rapidly build integrated, production-grade prototypes that translate complex industrial data into intuitive, actionable AI experiences.

Responsibilities

• Rapid DS Prototyping: Take early-stage ML models and RAG pipelines and transform them into interactive, full-stack "Alpha" products within days.
• Agentic UX Design: Architect front-end interfaces that allow users to interact with Agentic Workflowsdesigning how a plant engineer "talks" to a Root Cause Analysis (RCA) agent or probes a time-series plot.
• Data Translation: Deep-dive into customer datasets (SCADA, DCS, IoT) to perform exploratory data analysis (EDA) and immediately reflect those insights in a functional UI.
• Bridge to Engineering: Work with core Data Science to understand model constraints and with Engineering to ensure your high-fidelity prototypes are architected for scale (API-first, containerized).
• Design-Led Data Science: Apply design thinking to industrial problems, ensuring our AI solutions solve the right operational workflows (e.g., maintenance scheduling, process stability).

Key Skills

• Velocity-First Development: Expert proficiency in Cursor/Antigravity or similar AI-integrated IDEs to bypass boilerplate and build integrated features at 10x speed.
• The DS Stack: Strong foundation in Python, Polars/Pandas, and Scikit-learn. You should be comfortable enough with ML to tweak a model or optimize a RAG prompt.
• Industrial Intuition: You "get" the domainyou understand that a 2% drift in a sensor might be a critical failure or just noise, and you know how to design a UI that communicates that nuance.
• Full-Stack Data Ownership: You are comfortable managing the data flow from a PostgreSQL/TimescaleDB backend through a FastAPI layer and into a polished frontend.
• Product Sense: You can sit with a customer, look at their "messy" data, and sketch a solution that solves their pain point before the meeting ends.

Qualifications

• 3+ years of experience in a role that blended Data Science with Software Engineering (e.g., ML Engineer, Product Engineer, or DS Prototyper).
• A portfolio demonstrating end-to-end AI applicationswe want to see things youve built that people have actually clicked on.
• Prior experience in Industrial AI, Manufacturing, or Energy is highly preferred.
• A "Hacker" mindset: You love finding the shortest path between a complex data problem and a working solution