Senior Data Scientist(Gen AI)

ABOUT TIDE At Tide we help SMEs save time (and money) in the running of their businesses by not only offering business accounts and related banking services, but also a comprehensive set of highly usable and connected administrative solutions from invoicing to accounting. Tide is transforming the small business banking market with over 1.8 million members globally across the UK, India, Germany and France. Using advanced technology, all solutions are designed with SMEs in mind. With quick onboarding, low fees and innovative features, we thrive on making data-driven decisions to serve our mission: to help SMEs save both time (and money) so they can get back to doing what they love. Tide facts: Tide is available for UK, Indian, German and French SMEs Over 1.8 million members: 800,000 UK and 1,000,000 in India and growing rapidly Over $300 million raised in funding Over 2,500 Tideans globally - we’re diversity champions! We have offices in Central London, with a member support and technology centre in Sofia, Bulgaria, technology centres in Serbia, Romania, Lithuania and Hyderabad and offices in Gurugram and New Delhi, and in Berlin, Paris and Luxembourg. ABOUT THE ROLE A talented Data Scientist (DS-3) with generative AI expertise to contribute to the development and implementation of advanced AI solutions. You'll work on generative AI projects, applying your skills in LangChain, LangGraph, SQL, Python, AWS Bedrock, and Databricks to solve business challenges as part of our innovative team. As a Lead Data Scientist you’ll be: Implementation Development: Implement generative AI solutions leveraging AWS Bedrock and Databricks based on established architectural patterns Technical Execution: Apply your expertise in generative AI, LLMs, and related technologies to deliver high-quality solutions Cross-Functional Collaboration: Work with product, engineering, and business teams to understand requirements and implement effective AI solutions Statistical Analysis: Apply appropriate statistical methods to validate models and hypotheses Data Analysis: Conduct thorough exploratory data analysis and handle data quality issues effectively Feature Engineering: Implement feature engineering techniques for ML models, including dimensionality reduction and feature selection Model Development: Build and tune generative AI models using frameworks like LangChain and LangGraph with proper regularization techniques Intent Classification: Implement intent detection systems combining LLMs with data analysis techniques Response Generation: Develop components for generating structured responses by combining AI with business rules Continuous Learning: Stay current with generative AI techniques and apply new approaches to improve solutions Documentation Knowledge Sharing: Create clear documentation and share knowledge with team members Testing Validation: Thoroughly test generative AI applications to ensure they meet requirements and quality standards WHAT ARE WE LOOKING FOR 6+ years of experience in data science, machine learning, or related field 1+ years of hands-on experience with generative AI, large language models (LLMs), or natural language processing Experience with traditional NLP models and techniques Strong proficiency in Python and SQL for data retrieval and processing Solid understanding of statistics, hypothesis testing, and probability distributions Experience with LangChain, LangGraph for implementing AI workflows Understanding of prompt engineering, RAG (Retrieval Augmented Generation), and fine-tuning techniques for LLMs Experience implementing intent detection systems using generative AI Familiarity with rule-based systems to augment AI capabilities Experience with cloud platforms, particularly AWS services Familiarity with Knowledge Graphs for LLM use cases Knowledge of evaluation approaches for generative AI outputs Experience with Databricks or similar data processing platforms Nice to Have: Advanced deg ... (truncated, view full listing at source)