Ecozen is a technology company, and through our solutions, we are building a smart and sustainable future. We believe technology and innovations have the power to bring change and we look to harness this power to build solutions that deliver impact to our customers, our people and our planet.
Our products have revolutionized the irrigation and cold chain industries, with path-breaking innovations in predictive analytics, motor controls, energy storage, AI & IoT modules and food tech. Our technological innovations are now set to disrupt the EV, financial services and asset management industries as well.
We bring these innovations to market fast. How are we so fast? We actively collaborate and trust each other. We listen to our customers and learn fast and unlearn even faster. We predict (create) the future. And most importantly we empower our people with the ability to decide
As Data Scientist, you would be part of the IoT and Analytics team at Ecozen, which is building state of the art analytics for physical systems including Battery systems for EV and Energy Storage Systems
- You should be passionate to solve analytics problems using mix of Physics and data-based approaches as a full stack data scientist
- Explore different feature extraction methodologies and modelling approaches suitable to deliver required analytical insights
- Create production codes for data cleansing, manipulation, transformation followed by feature engineering and model development for real-world application
- Develop new monitoring indicators and their associated algorithms using time series prediction and anomaly detection techniques, with the final goal to deploy those using cloud-based tools.
- Bachelors in CS/Statistics/Electrical Engineering/Mechanical Engineering
- 3+ year of experience working with Data Science/AI based analytics with exposure to complete lifecycle of ML solution deployment.
- Hands-on data engineering and ML engineering including Data wrangling, Data cleaning, Data visualization , feature engineering, ML modelling and production of ML solutions.
- Knowledge in Statistics, probabilistic machine learning techniques (like Bayesian statistics, RVM etc.) in addition to standard ML techniques.
- Programming skills in Python and working knowledge of deep learning frameworks like TensorFlow, Pytorch, Keras, LSTM, CNN etc.
- Comfortable working with SQL/noSQL databases and AWS cloud services
- Good analytical, debugging and tracing skills and practical understanding of clean code principles (SOLID, DRY, KISS).
Good to have Skills:
- Background in Electrochemistry and experience in Battery modelling/simulations
- Prior experience working with large volume time series data and data from real devices
- Experience of building and working with APIs.
- Working knowledge of MLOps and model evaluation and monitoring techniques.