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 LinkedIn 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, Board Reporting and Analytics, the Senior Analyst will play an integral part in developing robust analytical solutions to generate insight of investment holdings, performance, and exposure. The Senior Analyst will apply both traditional data analysis skills and machine learning, large language models (LLM), and generative AI techniques to help provide deeper analytical insight, assist with process improvement and develop robust analytical solutions, and to generate insight of investment holdings, performance, and exposure.
NOTE: This is a contract position for 18 Months

What you will do:

• Analyze and model complex data from various workflow and multiple systems and make recommendations to produce key metrics to provide the Senior Management and Board with the information required to fulfill its oversight and governance role.
• Apply machine learning and generative AI techniques to provide investment performance insight, generate synthetic data, create realistic simulations, and enhance data analysis capabilities.
• Collaborate with other teams of the Department to identify business requirements; design and implement data-centric solutions to solve business problems and generate insights.
• Clean, preprocess, and analyze large datasets to extract meaningful insights and patterns.
• Participate in the design and building of a consolidated performance analytic tool to provide insights of investment performance related to the market condition and trading strategies.
• Develop and maintain a deep understanding of the Department’s internal operations, businesses, and processes, as well as industry best practices and emerging technologies in machine learning and lead the team in delivery.
• This role will support the Director in leading innovation, business process improvement, sparking an innovation mindset within the Department, and engaging external vendors to showcase innovation opportunities to the Department (such as artificial intelligence, robotic process automation, machine learning, etc.).
• Foster a culture of innovation and continuous learning within the team and contribute to the development of new data science initiatives and strategies.
• Stay current with the latest machine learning research and techniques, and with industry developments in machine learning and evaluate their potential impact on the organization.
• Lead research and identify new technologies, techniques, and methodologies that can be applied to the development of machine learning solutions.

What you bring:

• A Bachelor’s, Master’s degree or Ph.D. in Computer Science, Statistics, Data Science, or a related field
• 5+ years of experience in data engineering, data mining, and machine learning algorithms
• Strong data modeling, data processing, and data analysis skills.
• Extensive programming experience with Python and familiarity with machine learning packages and libraries.
• Familiarity with cloud technologies, along with hands-on experience in working with both cloud and on-premise databases. Experience with SQL, Snowflake, SAP HANA is especially desirable.
• Deep understanding of Natural Language Processing (NLP) and Large Language Models (LLMs).
• Good understanding of both public and private investment products. Previous experience working in financial institutions is an asset.
• Strong problem-solving skills and the ability to think critically and creatively to develop innovative solutions.
• Effective communication skills to elaborate models and translate the results into business recommendations.

• Analyze and model complex data from various workflow and multiple systems and make recommendations to produce key metrics to provide the Senior Management and Board with the information required to fulfill its oversight and governance role.
• Apply machine learning and generative AI techniques to provide investment performance insight, generate synthetic data, create realistic simulations, and enhance data analysis capabilities.
• Collaborate with other teams of the Department to identify business requirements; design and implement data-centric solutions to solve business problems and generate insights.
• Clean, preprocess, and analyze large datasets to extract meaningful insights and patterns.
• Participate in the design and building of a consolidated performance analytic tool to provide insights of investment performance related to the market condition and trading strategies.
• Develop and maintain a deep understanding of the Department’s internal operations, businesses, and processes, as well as industry best practices and emerging technologies in machine learning and lead the team in delivery.
• This role will support the Director in leading innovation, business process improvement, sparking an innovation mindset within the Department, and engaging external vendors to showcase innovation opportunities to the Department (such as artificial intelligence, robotic process automation, machine learning, etc.).
• Foster a culture of innovation and continuous learning within the team and contribute to the development of new data science initiatives and strategies.
• Stay current with the latest machine learning research and techniques, and with industry developments in machine learning and evaluate their potential impact on the organization.
• Lead research and identify new technologies, techniques, and methodologies that can be applied to the development of machine learning solutions