­Data Scientist ____ Toronto ON (3 Days/Week Onsite)____Contract

Role- Data Scientist

Location- Toronto ON (3 Days/Week Onsite)

Contract

We are hiring a Data Scientist with experience supporting sales enablement, ideally within the insurance industry, to contribute to data preparation, model development, and evaluation activities across several Group Benefits insurance initiatives.

Candidates should also be comfortable owning moderate scope analytics projects, translating data into business recommendations, and working across diverse data systems.

Job Description

Responsibilities

• Prepare, clean, and analyze datasets for ML/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 feature engineering pipeline for ML/AI models.
• Collaborate with business stakeholders to understand workflows, data requirements, and key performance metrics.
• Build dashboards and reporting assets to serve insights to business stakeholders.
• Contribute to development and evaluation of modular Gen AI features (RAG systems, NL-to-SQL, agentic workflows).
• Develop and implement analytics enabled solutions that support business goals and process improvement; deliver complete projects of moderate complexity.
• Translate analytical findings into business language and recommend solutions to stakeholders and leadership.
• Document data sources, contribute to structured processes, and support closed loop tracking for continuous improvement.

Qualifications

• 3-5 years of experience working as a Data Analyst, Data Scientist, or in a related analytical role, ideally in an insurance, sales support, or finance environment.
• Strong Python skills, including experience with data science libraries (e.g., pandas, NumPy, scikit learn, PySpark or similar).
• Strong SQL experience and proficiency with data modeling concepts.
• Proficiency with BI tools such as Power BI, Tableau, or similar platforms.
• Demonstrated experience engineering complex features from large, messy, and multi source datasets and to assess feature quality.
• Demonstrated experience in end to end model development: problem framing, data preparation, feature engineering, model training, validation, and deployment support.
• Experience with classical statistical methods and ML techniques (e.g., regression, clustering, PCA, decision trees, survival analysis).
• Ability to translate ambiguous business questions into structured analytical approaches.
• Curiosity about GenAI and eagerness to learn LLM related workflows, evaluation techniques, and best practices.
• Bachelors degree in Statistics, Math, Computer Science, Engineering, or equivalent technical experience.
• Ability to communicate insights clearly to business partners and contribute to solution ideation within broader business strategy.

Candidate Requirements

Must-Have Skills –

• Strong Problem-Solving Mindset
• ML Fundamentals (Exploratory Datal Analysis, Feature Eng, Model Testing)
• GitHub, Git
• LLM (Context Engineering, Prompt Engineering and LLM Guardrails)
• Good communication skills (Be able to translate complex technical components into simple business requirements, so that the business understands)

Nice-to-have Skills-

• MLOps
• Azure & Databricks
• Agentic AI