Senior Data Scientist - Product Data

Join us to solve hard problems using the full spectrum of modern AI. We are looking for a Data Scientist who can seamlessly switch between training deep neural networks from scratch and orchestrating complex, agentic LLM workflows. This role takes you beyond classical fintech, challenging you to apply advanced AI to product data and comparable shopping. It is a hands-on, technical position where theoretical depth meets engineering reality, and where you will build autonomous systems and custom models that drive real business value.

What You Will Do

• Build u0026amp; Deploy Models: Own full design, training, and deployment of Neural Networku0026nbsp; models using frameworks like TensorFlow or PyTorch to solve diverse business challenges.

• Develop Agentic Workflows: Architect and implement autonomous AI agents capable of reasoning, planning, and executing multi-step tasks to automate complex workflows.

• Leverage LLMs: Fine-tune and orchestrate Large Language Models for varied use cases, integrating them into robust applications.

• Bridge Theory u0026amp; Practice: Apply a strong theoretical understanding of Machine Learning to practical problems, ensuring solutions are not just academically sound but robust, scalable, and valuable to the business.

• End-to-End Ownership: Take ownership of the full ML lifecycle, from data pipeline construction and feature engineering to model monitoring and continuous improvement in production.

• Collaborate u0026amp; Innovate: Work closely with engineers and product teams to identify opportunities where advanced AI can drive significant impact, while staying ahead of the curve on SOTA research.

Who You Are

• Strong Technical Foundation: You have a solid grasp of computer science fundamentals and software engineering principles. You write clean, production-ready code (Python is a must).

• Deep Learning Expertise: You have hands-on experience building and training Deep Neural Networks and are proficient with deep learning frameworks such as TensorFlow, Keras, or PyTorch.

• LLM u0026amp; Agentic Experience: You are familiar with the modern LLM stack (e.g., Hugging Face, OpenAI API) and have experimented with or built agentic systems (using tools like LangChain, AutoGen, or custom implementations).

• Pragmatic u0026amp; Theoretical: You balance deep theoretical knowledge of how models work (mathematics, optimization, probability) with a pragmatic