Responsibilities
- Develop methods for efficient transfer and processing of structured and unstructured data from product data stores.
- Conduct rigorous Testing and Validation of models, ensuring accuracy, reliability, and scalability in real-world lending scenarios.
- Drive end-to-end model deployment, working closely with software engineers to integrate models into production systems and monitor their performance.
- Deploy ML models into production using cutting-edge deployment strategies, and conduct A/B tests to objectively measure improvements.
- Continuously monitor and evaluate model performance and provide insights into the model.
- Keep innovating and optimising the machine learning workflow, from data exploration and model experimentation/prototyping to production.
- Apply cutting-edge technologies and toolchains in big data and machine learning to build a machine learning platform on the cloud (ML ops).
Requirements
- Minimum 4+ years of total working experience with Machine Learning, Statistical Modelling, and Statistical Analysis.
- Strong in data structures and algorithms, with excellent problem-solving ability and programming skills.
- Experience in applied machine learning, familiar with one or more of the algorithms such as ML Modelling and validation, Model Experimentation and Testing, Drawing Inferences and Insights, etc.
- Experience in Java/ Python; at least one of the Big Data tools (For eg, Hive SQL/ Spark/ MapReduce; at least one of the ML libraries (e. g. sci-kit-learn, TensorFlow, PyTorch).
- Experience in developing reusable ML models and ensuring scalability and modernisation, Model Validation, Experimentation, Deployment and Testing.
- Possess strong communication skills, positive mindset, good teamwork skills, and eagerness to learn/implement new technology and experiment.
- Experience with unstructured data like images and text is a plus.
This job was posted by Krishna Chaitanya Bandaru from Unify.
