Data Scientist - Python, LLM, AI

FP Inc.

Toronto, ON, Canada
Contract
Hybrid
C$60 - C$70
PythonLarge Language Models (LLMs)Agentic AI frameworks (e.g. LangChain agents, AutoGen)

Role Overview

We are seeking a highly skilled Data Scientist - Python, LLM, AI, to join our banking team, focusing on the development and deployment of Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems. This role is pivotal in bridging the gap between traditional deterministic AI and modern generative models to enhance banking operations, customer interactions, and internal knowledge management.

Key Responsibilities

  • Model Development & Fine-tuning: Design, develop, and fine-tune specialised LLMs and NLU techniques for banking use cases, including multi-turn dialogue management and financial text summarisation.
  • System Architecture: Build and optimise intelligent, agentic conversational AI systems and RAG architectures to ensure accurate, grounded, and explainable AI responses.
  • Data Engineering: Gather, clean, and preprocess large datasets for LLM training, ensuring data quality, consistency, and strict compliance with regulatory and privacy standards.
  • Performance Monitoring: Evaluate model performance using advanced metrics, mitigating bias, and continuously re-training models to adapt to changing market dynamics.
  • Stakeholder Collaboration: Lead the operationalisation of hybrid architectures and communicate complex technical findings to both technical and non-technical stakeholders through reporting and dashboards.

Candidate Requirements/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