Data Scientist in Toronto

W e are seeking a Data Scientist with experience supporting sales workflows, ideally within the insurance industry, to contribute to data preparation, insight generation, and evaluation activities for our Gen AI-powered sales enablement platform.

This role blends strong analytical skills with an understanding of advisor and sales team operations, requiring ownership of moderate-scope analytics projects, translation of data into business recommendations, and collaboration across diverse data systems.

Key Responsibilities

• Prepare, clean, and analyze datasets for training, validating, and evaluating Gen AI/LLM features.
• Collaborate with product, sales, and business stakeholders to understand workflows, data requirements, and performance metrics.
• Build dashboards and reporting assets to track adoption, performance, and business impact.
• Support prompt evaluation, annotation, and quality assurance tasks for AI outputs.
• Contribute to structured knowledge bases, taxonomies, and metadata supporting RAG systems.
• Generate actionable insights to optimize sales processes and improve advisor/end-user experiences.
• Deliver analytics-enabled solutions that support business goals and process improvement.
• Analyze complex datasets and connect data sources across multiple internal systems.
• ranslate analytical findings into business language and recommend solutions to stakeholders.
• Document data sources, contribute to structured processes, and support closed-loop tracking.
• Engage subject matter experts to understand business processes and build collaborative networks.
• Provide guidance and mentorship to junior analysts or data scientists.
• Required Qualifications
• 3–5 years of experience as a Data Analyst, Data Scientist, or in a related analytical role.
• Proficiency with BI tools (Power BI, Tableau, or similar).
• Background working with sales datasets; insurance industry exposure is a plus.
• Ability to translate ambiguous business questions into structured analytical approaches.
• Bachelor’s degree in Statistics, Math, Computer Science, Engineering, or equivalent technical experience.
• Working knowledge of classical statistical methods (regression, clustering, PCA, decision trees, survival analysis).
• Familiarity with machine learning techniques and AI/ML toolkits.
• Experience navigating large, diverse datasets using structured analytical methods.
• Comfort with data modeling concepts and relational databases.
• Strong communication skills to translate technical insights into business recommendatio ns.
• Preferred Qualifications (if any)
• Curiosity about Gen AI and eagerness to learn LLM workflows, evaluation techniques, and best practices.
• Experience with MLOps, Azure, Databricks, or RAG pipelines.

Certifications (if any)

• None required; relevant technical certifications are an asset.
• Typical Day
• Participate in daily project updates with the core team.
• Communicate with business partners to confirm requirements and timelines.
• Propose and implement technical solutions based on business needs.
• Perform hands‑on data preparation, analysis, and development tasks.
• Draft Power Point slides outlining solutions for business stakeholders.
• Log tasks accurately in Jira.
• Collaborate with a project team of 4–5 members plus the Data Infrastructure team.
• Report directly to the Project Team Lead.
• Candidate Requirements
• Mu st-Have Skills
• Strong problem‑solving mindset
• Strong communication skills to translate technical concepts into business lang uage
• Nice-to-Have Skills
• MLOps
• Years of Experience
• 3–5 years
• Degrees/Certifications Required
• Bachelor’s degree in Statistics, Math, Computer Science, Engineering, or equivalent technical experience
• Lack of ownership or initiative
• Measures of Success
• Ability to accurately assess effort required for tasks without deviating from scope or timelines.
• Effective handling of blockers and escalations with feasible alternatives.
• Delivery of actionable insights and analytics solutions that improve sales workflows.
• #J-18808-Ljbffr