GenAI Developer

High-impact role in the insurance sector focused on advanced data analysis and GenAI-driven sales enablement. Leverage Python, BI tools, and machine learning concepts to transform complex datasets into actionable insights, build performance dashboards, and support AI-powered solutions in a collaborative hybrid environment.

What is in it for you:

• Salaried: $45-53 per hour.
• Incorporated Business Rate: $54-62 per hour
• 7-month contract.
• Full-time position: 37.50 hours per week.
• Hybrid: 3 days/week in Toronto office.

Responsibilities:

• Prepare, clean, and analyze datasets used for training, validating, and evaluating LLM-based or GenAI 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 of sales enablement tools.
• Support prompt evaluation, annotation, and quality assurance to ensure accuracy and reliability of AI-generated outputs.
• Contribute to structured knowledge bases, taxonomies, and metadata supporting RAG-based systems.
• Generate insights to optimize sales processes and improve advisor and end-user experiences.
• Develop and implement analytics solutions aligned with business goals and deliver projects of moderate complexity.
• Analyze complex datasets and connect multiple internal data sources.
• Translate analytical findings into business recommendations for stakeholders and senior data scientists.
• Document data sources, support structured processes, and enable continuous improvement tracking.
• Engage subject matter experts and contribute to collaboration and knowledge sharing.
• Provide guidance and feedback to junior analysts or data scientists when required.
• Participate in daily project updates and communicate with business partners on requirements and timelines.
• Propose and implement technical solutions aligned with business needs and deadlines.
• Perform hands-on data preparation, analysis, and development tasks.
• Prepare presentation materials to communicate proposed solutions.
• Track tasks and progress using Jira.

What you will need to succeed:

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or equivalent technical experience.
• 3 to 5 years of experience in a data analyst, data scientist, or related analytical role.
• Experience in sales support or sales operations environments, with exposure to insurance industry workflows considered an asset.
• Strong Python programming skills.
• Proficiency with BI tools such as Power BI, Tableau, or similar platforms.
• Knowledge of statistical methods and familiarity with machine learning techniques.
• Experience working with large and complex datasets using structured analytical approaches.
• Understanding of data modeling concepts, relational databases, and basic AI/ML toolkits.
• Familiarity with GitHub and version control practices.
• Knowledge of ML fundamentals including exploratory data analysis, feature engineering, and model testing.
• Exposure to LLM concepts such as prompt engineering, context engineering, and guardrails.
• Ability to translate complex technical concepts into clear business insights.
• Strong problem-solving skills and ability to work autonomously.
• Effective communication skills and ability to collaborate within a team environment.
• Curiosity and willingness to learn GenAI workflows and evaluation techniques.

Why Recruit Action?

Recruit Action (agency permit: AP-2504511) provides recruitment services through quality support and a personalized approach. As part of the screening process, some applications may be reviewed using artificial intelligence tools. Only candidates who meet the hiring criteria will be contacted.

Pay: $45.00-$62.00 per hour

Benefits:

• Work from home

Application question(s):

• This role is hybrid in Toronto — are you comfortable working 3 days per week in-office?

Experience:

• Python (pandas, data processing, scripting): 3 years (required)
• ML basics (EDA, feature engineering, testing): 2 years (required)
• LLM / GenAI (prompting, context, evaluation): 2 years (required)
• Data analysis (complex, multi-source datasets): 3 years (required)
• BI tools (Power BI, Tableau, dashboards and reporting): 2 years (required)
• Git / GitHub (version control, collaboration): 2 years (required)
• Azure / Databricks (cloud data and analytics environment): 1 year (preferred)
• RAG pipelines (retrieval, vector databases, knowledge bases): 1 year (preferred)
• MLOps (model deployment, monitoring, pipelines): 1 year (preferred)
• Sales / CRM data (sales operations, advisor workflows): 1 year (preferred)
• Insurance or financial services domain: 1 year (preferred)

Work Location: Hybrid remote in Toronto, ON M4W 1E6