Job Description

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 and 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 Cloud (ML ops).
• Experience with unstructured data like images & text is a plus

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 Modeling and validation, Model Experimentation & 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 Develop reusable ML models and ensure scalability and modernisation, Model Validation, Experimentation, Deployment & Testing
• Possess strong communication skills, positive mindset, good teamwork skills, and eagerness to learn/implement new technology and experiment.