You’ll work at the intersection of Generative AI, Machine Learning, and personal finance. You’ll partner with Product, Engineering, and Ops to:

• Drive smarter decision-making using AI.

• Improve customer outcomes by personalising experiences.

• Launch agentic AI systems to streamline sales, support, and credit evaluation.

• Design, build, and deploy machine learning and generative AI models.
• Translate real-world business problems into data science solutions — from ideation to production.
• Collaborate with engineers to set up scalable data pipelines and APIs.
• Constantly monitor model performance and retrain as needed.
• Build solutions that leverage LLMs for tasks like summarization, sentiment detection, classification, and recommendations.
• Stay up-to-date with developments in GenAI and actively experiment with new techniques.
  

• Strong foundation in machine learning, feature engineering, and model deployment.
• Hands-on experience implementing GenAI use cases (e.g., prompt engineering, RAG, embeddings).
• Proficiency in Python, SQL, and ML libraries like scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Familiarity with LLM frameworks (LangChain, OpenAI, HuggingFace) and cloud services (AWS/GCP/Azure).
• Demonstrated ability to take AI models from notebook to production.
• Excellent communication skills and ability to collaborate cross-functionally.

• Prior experience in Fintech, BFSI, or working with credit and customer data.
• Understanding of ethical AI, data privacy, and model fairness.
• Familiarity with customer-facing AI products (chatbots, agentic workflows).

• A high-impact role at a company solving a real societal problem.

• The opportunity to shape AI strategy and product direction from the ground up.

• A culture that values curiosity, ownership, and bold thinking.