Data Scientist

Compunnel Inc.; Toronto; On-site; CAD 85,000 - 110,000; Full time

Job summary

A data science company is seeking a Data Scientist in Toronto, Ontario to support a GenAI-powered sales enablement platform. The successful candidate will analyze complex datasets, generate insights, and collaborate with cross-functional teams. Key qualifications include strong proficiency in Python and SQL, experience with BI tools, and a degree in a technical field. This role requires excellent analytical and programming skills, with opportunities to enhance sales workflows through AI-driven insights.

Qualifications

• 3–5 years of experience as a Data Scientist, Data Analyst, or in a related analytical role.
• Strong proficiency in Python for data analysis and machine learning workflows.
• Strong SQL skills and experience working with relational databases.
• Experience with exploratory data analysis and feature engineering.
• Bachelor’s degree or equivalent technical experience.

Responsibilities

• Prepare, clean, and analyze datasets for training and evaluating LLM models.
• Build dashboards and reporting solutions for sales tools' performance.
• Generate insights to enhance sales processes and end-user experiences.
• Collaborate with cross-functional teams to understand data needs.

Skills

Python

SQL

Analytical skills

Problem-solving

Collaboration

Education

Bachelor’s degree in Statistics, Mathematics, Computer Science, or Engineering

Tools

Power BI

Tableau

Git

Job description

The Data Scientist will support the development and optimization of a GenAI-powered sales enablement platform designed to help sales advisors interact with enterprise data through a conversational interface. This role focuses on preparing and analyzing complex datasets, generating insights, and supporting evaluation processes for LLM-driven features. The Data Scientist will collaborate with product, sales, and engineering teams to improve data pipelines, enhance analytics capabilities, and ensure reliable AI-driven insights that support sales workflows. The position requires strong analytical and programming skills, hands-on experience with Python, SQL, and modern data platforms, and familiarity with LLM integrations and machine learning techniques.

KEY RESPONSIBILITIES

• Prepare, clean, and analyze datasets used for training, validating, and evaluating GenAI and LLM-based features
• Collaborate with product, sales, and business stakeholders to understand advisor workflows, data needs, and key performance metrics
• Build dashboards and reporting solutions to track adoption, performance, and business impact of sales enablement tools
• Support prompt evaluation, annotation, and quality assurance processes to improve AI-generated outputs
• Contribute to the development of structured knowledge bases, taxonomies, and metadata to support RAG-based systems
• Generate insights to improve sales processes and enhance advisor and end-user experiences
• Develop analytics-driven solutions that support business goals and operational improvements
• Analyze large and complex datasets and connect multiple internal data sources for unified insights
• Translate analytical findings into clear business recommendations for stakeholders
• Document data sources, methodologies, and processes to support continuous improvement
• Collaborate with subject matter experts to understand business processes and develop analytical approaches
• Assist with ongoing improvement of data pipelines and LLM integration with conversational interfaces
• Support optimization of data and LLM pipelines that power the internal Data Copilot platform
• Log tasks and project updates using collaboration tools such as Jira
• Provide guidance and feedback to junior analysts or data scientists when needed

REQUIRED QUALIFICATIONS

• 3–5 years of experience as a Data Scientist, Data Analyst, or in a related analytical role
• Strong proficiency in Python for data analysis and machine learning workflows
• Strong SQL skills and experience working with relational databases
• Hands‑on experience with Git version control including branching and pull requests
• Experience with exploratory data analysis, feature engineering, and model evaluation techniques
• Proficiency with BI tools such as Power BI, Tableau, or similar visualization platforms
• Experience working with complex datasets across multiple systems
• Familiarity with LLM implementations, prompt engineering, and LLM guardrails
• Strong problem‑solving skills and the ability to translate complex technical findings into business insights
• Ability to work independently and manage loosely defined tasks in a fast‑paced environment
• Strong communication and collaboration skills for working with cross‑functional teams
• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or equivalent technical experience

PREFERRED QUALIFICATIONS

• Experience working with Databricks, Spark, or modern data engineering platforms
• Exposure to RAG pipelines or GenAI data architectures
• Experience with Azure cloud environments
• Familiarity with MLOps practices
• Background working with sales datasets or sales operations workflows
• Exposure to insurance industry data models or advisor‑based business environments