Data Scientist – Python, LLM, AI

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JOB DESCRIPTION

Location: Hybrid | Downtown, Toronto

Duration: 6 Months 

Our client, a leading financial institution in Downtown Toronto, is looking for a Data Scientist – Python, LLM, AI to Gather and clean relevant data sets for training and fine-tuning Large Language Models (LLMs), and building Retrieval Augmented Generation (RAG) systems. The successful candidate will have the opportunity to work with one of the Top 5 Banks in Canada.

Typical Day in role:

• Determine the “right tool for the job”—balancing the precision of deterministic AI with the flexibility of RAG and AI models.
• Ensure data quality, consistency, and compliance with regulatory requirements.
• Develop and fine-tune specialized Large Language Models (LLMs) and advanced Natural Language Understanding (NLU) techniques for diverse banking use cases, including complex information extraction, multi-turn dialogue management, and financial text summarization.
• Design, develop, and optimize intelligent, agentic conversational AI systems (e.g., advanced virtual assistants, automated financial advisors) leveraging LLMs for seamless customer interactions across various channels, including text and voice.
• Implement and refine advanced Natural Language Understanding (NLU) and Natural Language Generation (NLG) techniques, particularly within Retrieval Augmented Generation (RAG) architectures, to enhance the accuracy, relevance, and explainability of AI responses by grounding them in authoritative data sources.
• Assist in the strategic implementation and deployment of Large Language Models (LLMs) for a wide array of banking applications beyond just customer interfaces, such as automated content generation (e.g., reports, summaries of financial documents), risk assessment insights, and internal knowledge management.
• Analyze interactions with LLM-powered agents and RAG systems to identify emergent patterns, user needs, and critical areas for performance optimization and continuous improvement.
• Generate actionable insights derived from LLM and Agentic AI analysis to strategically inform business decisions and drive innovation.
• Evaluate model performance using relevant metrics and develop strategies for model optimization and bias mitigation.
• Continuously monitor, update, and re-train models to adapt to changing customer behavior, market dynamics, and evolving data landscapes.
• Create dashboards and reporting for a diverse range of stakeholders.
• Ensure strict adherence to data privacy and security standards, especially when handling sensitive customer data within generative AI systems.
• Lead the operationalization of Hybrid Architectures where traditional Intent-based bots meet Generative AI.

Documentation and Reporting:

• Maintain comprehensive documentation of data sources, LLM/RAG model development, prompt engineering strategies, and implementation processes.
• Provide regular reports and updates on AI solution performance and project progress to the team and management.
• Collaboration and Communication:
• Work closely with cross-functional teams to seamlessly integrate cutting-edge AI solutions into core banking operations.
• Effectively communicate complex technical findings, project progress, and challenges to both technical and non-technical stakeholders.
• Ensure that all AI solutions comply with banking regulations and ethical AI standards, particularly regarding customer data transparency and responsible use of generative models.
• Conduct rigorous testing, validation, and quality assurance for LLM-powered and Agentic AI solutions to ensure accuracy, fairness, and a seamless customer experience.
• Proactively identify and address potential risks and challenges that arise during the development and deployment of advanced AI systems.

Must Have Skills:

• 5- 8 years of experience with Python for data analysis, modeling, and scripting.
• 5-8 years of experience with SQL for data manipulation and querying.
• 2-5 years of experience in data preprocessing techniques, including data cleaning, transformation, and vectorization.
• 2-5 years of experience in data mining, data profiling, modeling, cleansing, and enriching as well as extracting, transforming, loading (ETL) solutions.
• 2-5 of experience in data privacy and security standards, especially when handling sensitive customer data within generative AI applications.

Nice-To-Have Skills:

• Demonstrable experience or a strong theoretical understanding of Large Language Models (LLMs), including fine-tuning, prompt engineering, and an awareness of their current capabilities and limitations.
• Familiarity with or understanding of Retrieval Augmented Generation (RAG) architectures and their implementation for grounded, factual AI responses
• Familiarity with Agentic AI frameworks (e.g., LangChain agents, AutoGen) or designing multi-step AI reasoning processes
• Familiarity with Google Cloud Platform (GCP) or other cloud computing environments.

Soft Skills Required:

• Strong communication and presentation skills for effective interaction with clients, vendors, and management.
• Ability to prioritize tasks, plan, and manage projects effectively in a fast-paced environment.
• Collaboration in diverse teams and settings
• Creative, collaborative mindset with keen attention to detail
• Time Management skills

Education:

• Highest Education

FP Inc. is committed to creating an inclusive environment where all team members and clients feel like they belong. In accordance with the requirements set out in the Employment Standards Act, FP Inc. hereby declares that AI is utilized in the screening process for this position. The hourly compensation range for this role is $60/hr -$70/hr. We seek applicants with a wide range of abilities, and we provide an accessible candidate experience. We advocate for you and welcome anyone regardless of race, colour, religion, national origin, sex, physical or mental disability, or age.