About Coulomb

At Coulomb AI, we envision a future powered by the seamless integration of AI and Battery Technologies, creating a powerful synergy to combat climate change. We build category-leading software that can significantly improve battery lifespan and performance by employing advanced predictive analytics, real-time monitoring, and adaptive battery management algorithms.

Coulomb is headquartered in San Francisco with its development and research center in Bangalore. Founders [Khushboo Shrivastava][1] and [Santanu Mondal][2] are alumni of IIT Bombay and have first-hand experience working on first-generation Electric Vehicles at General Motors. We are backed by some of the best climate tech investors in the world, including Y Combinator, Harvard Management Seed Capital, CSVE Ventures, and prominent Silicon Valley-based Angels.

We already have a global presence with customers in 5 countries across UK, US, APAC and India

About the Role

Being part of the founding team, you will have the opportunity to shape the future of sustainable energy. If you are a data scientist with a passion for leveraging your skills to drive positive environmental change, we encourage you to apply and be a key player in shaping the future of electric transportation.

As a Lead Data Scientist, here’s what you’ll be doing

• Build novel predictive models on real-time data streams
• Develop and deploy machine learning models at scale, navigating the challenges presented by large and complex datasets
• Actively assist in building systems to continuously track model performance, ensuring models remain effective in dynamic environments
• Communicate findings and insights to technical and non-technical stakeholders
• Implement effective debugging tools and practices to diagnose and address performance issues or unexpected behaviors
• Maintain up-to-date documentation on model maintenance procedures, troubleshooting guides, and best practices

We are excited about you because you have

• 3+ years of hands-on experience in data science, with a focus on Big Data Exploration, Summarization, and ML Deployment
• Successfully delivered at least one product or pivotal feature, actively involved in business problem identification, researching, sourcing necessary data, and constructing data pipelines
• Strong grasp of end-to-end data science practices, encompassing data cleaning, exploratory data analysis (EDA), feature engineering, model training, testing, and deployment using ML libraries and frameworks in Python
• Adept at utilizing SQL for comprehensive analysis

You’ll be a great fit if additionally, you have

• Knowledge of big data technologies (e.g., Hadoop, Spark) and experience with distributed computing
• Experience deploying ML models in production, including knowledge of model deployment and optimization
• Previously worked in a startup environment and have a high degree of ownership and appetite for ambiguity Like being a part of a high-performing team focussed on fast-paced execution at the same time detail-oriented