Senior Analyst, Fund Data Science and Modeling

Position: Senior Analyst, Total Fund Data Science and Modeling
Why you’ll love working here:high-performance, people-focused culture our commitment that equity, diversity, and inclusion are fundamental to our work environment and business success, which helps employees feel valued and empowered to be their authentic selves learning and development initiatives, including workshops, Speaker Series events and access to Linked In Learning, that support employees’ career growth membership in HOOPP’s world class defined benefit pension plan, which can serve as an important part of your retirement security competitive, 100% company-paid extended health and dental benefits for permanent employees, including coverage supporting our team's diversity and mental health (e.g., gender affirmation, fertility and drug treatment, psychological support benefits of $2,500 per year, parental leave top-up, and a health spending account).optional

post-retirement health and dental benefits subsidized at 50% yoga classes, meditation workshops, nutritional consultations, and wellness seminars the opportunity to make a difference and help take care of those who care for us, by providing a financially secure retirement for Ontario healthcare workers

Job Summary:

Reporting to the Director, Data Science & Modeling, Total Fund Analytics, the Senior Analyst will bring deep expertise in applied AI and LLM/RAG-enabled analytics to advance investment reporting, enhance analytical insight generation, and enable governed natural-language access to investment data. The role will design, build, and scale AI-enabled reporting capabilities on top of governed data foundations, semantic metric layers, analytical data models, and curated investment datasets.

This role will also be responsible for improving data warehouse structures, data marts, curated aggregation layers, semantic metric layers, and modern data engineering practices across the reporting ecosystem.

What you will do:

Total Fund Data Science & Modeling Design, build, and maintain reliable ETL/ELT ingestion and transformation pipelines across data systems such as SAP HANA, Snowflake, Microsoft Fabric, and other enterprise data platforms, with sufficient production discipline to support governed reporting and AI-enabled consumption.

Design, develop, and maintain analytical and semantic data models, including dimensional structures, curated aggregation layers, metric views, and reusable datasets that make key investment metrics consistently retrievable across reporting, analytics, and AI interfaces.

Extend the semantic metric layer used by Power BI, Qlik, natural language interfaces, and other tools, ensuring that LLM/RAG solutions retrieve accurate and governed definitions, versioned metrics, and roll-ups with streamlined business logic.

Analyze, model, and curate complex data from multiple workflows and systems to produce trusted key metrics, insights, and recommendations that support Senior Management and the Board to fulfill its oversight and governance role.

Embed data quality, lineage documentation, reconciliation controls, metric definitions, and model documentation into pipeline and curated-layer design to support trusted investment reporting.

Apply AI-assisted development of statistical analysis, machine learning, and traditional data science techniques to accelerate analytical prototyping, identify investment result drivers, create simulations, and enhance investment reporting insight.

Research & Development Collaborate with Finance, investment, technology, and data stakeholders to identify business requirements, natural language analytics opportunities, and data-centric solutions that solve practical reporting and decision-support problems.

Participate in the design and building of consolidated investment analytics capabilities, including curated data products, analytical marts, semantic models, and cube-like structures that explain investment results in relation to market conditions, trading strategies, asset mix, and portfolio exposures.

Develop and maintain a deep understanding of Total Fund Analytics internal operations, investment reporting processes, institutional investment products, and emerging AI, data science, and analytics…