Data Scientist - Machine Learning & GenAI

Data Scientist – Machine Learning & GenAI

Work on high-visibility AI and data initiatives within the insurance sector, combining machine learning, GenAI, predictive analytics, and modern data tools to support strategic business decisions. This hybrid opportunity offers a collaborative and fast-paced environment where innovation, problem-solving, and impactful analytics are at the center of every project.

What is in it for you:

• Salaried: $60-70 per hour.

• Incorporated Business Rate: $70-80 per hour.

• 6-month contract with the potential for permanent employment.

• Full-time contract position based in Toronto, Ontario.

• Day schedule, 37.50 hours per week.

• Enjoy the flexibility of hybrid work.

Responsibilities:

• Prepare, clean, and analyze datasets for ML and AI features from complex and fragmented internal data sources.

• Leverage LLMs to create features from unstructured data.

• Design and build segmentation and predictive models for customer and advisor analytics.

• Own the feature engineering pipeline for ML and AI models.

• Collaborate with business stakeholders to understand workflows, data requirements, and key performance metrics.

• Build dashboards and reporting assets to deliver insights to business stakeholders.

• Contribute to the development and evaluation of modular GenAI features, including RAG systems, NL-to-SQL solutions, and agentic workflows.

• Develop and implement analytics-enabled solutions supporting business goals and process improvement initiatives.

• Translate analytical findings into business language and recommend solutions to stakeholders and leadership teams.

• Document data sources, contribute to structured processes, and support continuous improvement tracking activities.

• Participate in daily project updates with the core team.

• Communicate with business partners to confirm requirements and clarify timeline constraints.

• Propose and implement technical solutions aligned with business needs and project deadlines.

• Perform hands-on data preparation, analysis, and development activities.

• Draft presentation materials outlining proposed solutions for business stakeholders.

• Accurately track and manage tasks within Jira.

What you will need to succeed:

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or equivalent technical experience.

• 3-5 years of experience as a Data Analyst, Data Scientist, or in a related analytical role within insurance, sales support, finance, or similar environments.

• Strong Python programming skills with experience using libraries such as pandas, NumPy, scikit-learn, PySpark, or similar tools.

• Strong SQL experience and proficiency with data modeling concepts.

• Experience with BI tools such as Power BI, Tableau, or similar platforms.

• Demonstrated experience engineering complex features from large, multi-source datasets and assessing feature quality.

• Experience with end-to-end model development, including problem framing, data preparation, feature engineering, model training, validation, and deployment support.

• Experience with statistical methods and machine learning techniques such as regression, clustering, PCA, decision trees, and survival analysis.

• Strong understanding of ML fundamentals, including exploratory data analysis, feature engineering, and model testing.

• Experience with GitHub and Git version control tools.

• Knowledge of LLM concepts, including context engineering, prompt engineering, and LLM guardrails.

• Ability to translate ambiguous business questions into structured analytical approaches.

• Ability to communicate technical concepts clearly to business stakeholders and translate complex technical components into understandable business requirements.

• Strong problem-solving mindset with the ability to make confident technical decisions.

• Ability to work autonomously, demonstrate ownership, and appropriately escalate issues when required.

• Curiosity about GenAI technologies and eagerness to learn LLM workflows, evaluation techniques, and best practices.

• Experience with MLOps, Azure, Databricks, or Agentic AI is considered an asset.

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.