OTPP

DataScientist

$105–155k Toronto, Ontario, Canada FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Scientist at OTPP. Skills: Machine learning, AI development, Statistical modelling, Data science. Participate in machine learning and AI development lifecycle. Design AI-enabled solutions”

Industry & Context.

Problems you'll solve

Problem-solving skills

What They're Looking For.

Must Have

Bachelor's degree in quantitative discipline, Proficient Python programming skills, Proficient SQL skills, Proficient Git workflow

Nice to Have

Master's or Ph.D. degree in quantitative discipline, Experience with large language models, Experience with mathematical optimization techniques, Experience in investments, Experience in capital markets, Experience in private equity, Experience in private markets

What You'll Do.

Participate in machine learning and AI development lifecycle

Design AI-enabled solutions

Build AI-enabled solutions

Evaluate AI-enabled solutions

Implement LLM-based engineering best practices

Develop machine learning techniques

Apply statistical modelling techniques

Apply mathematical optimization techniques

Translate business objectives into solution approaches

Champion coding standards

Contribute to building best practices

Share reusable patterns

Share lessons learned

Stay up to date with technologies

Explore new techniques

Experiment with new tools

Experiment with new models

Experiment with new data sources

Provide recommendations to business

Collaborate on research

Collaborate on analysis

Collaborate on experimentation

Develop independent insights

Build partnerships with business stakeholders

Drive data-driven solutions

Drive AI-enabled solutions

Drive optimization-based solutions

Support delivery of reports

Support delivery of analytics

Support delivery of models

Support delivery of visualizations

Support delivery of prototypes

Support delivery of decision-support tools

Identify opportunities to enhance AI/ML approaches

Identify opportunities to enhance optimization approaches

Leverage new techniques

Leverage emerging tools

Leverage alternative data sources

How You'll Work.

Team & Collaboration

Collaborating with data scientists; Collaborating with engineers; Collaborating with business stakeholders; Cross-functional teams; Business partners; Data partners; Technology partners

Communication Scope

Articulate thoughts; Articulate ideas

Full Job Description

## **The opportunity** We are seeking a talented and driven Data Scientist to join our team. The successful candidate will work with Private Markets Teams to build solid data and analytics foundation: derive insights from data, interpretdata, and develop statistical models as needed and contribute to overall data science capabilities. This role reports to the director of private investments technology and works with the private markets business group and the AI COE to identify, design, implement and maintain AI solutions, machine learning algorithms, statistical model development and related technologies. The Data Scientist also participates in data science practices and capability development at OTPP. If you are passionate about solving challenging problems and thrive in a fast-paced, high-stakes environment, we want to hear from you. ## **Who you 'll work with** You’ll work closely with the Data & Analytics team, collaborating with data scientists, engineers, and business stakeholders to develop and deliver analytics and AI-driven solutions. In this highly collaborative environment, you’ll help turn complex data into actionable insights, support machine learning initiatives, and contribute to enhancing the organization’s data science capabilities. ## **What you 'll do** * Actively participate in the end-to-end machine learning and AI development lifecycle, from experimentation and prototyping to deployment, monitoring, and continuous improvement * Design, build, and evaluate AI-enabled solutions using large language models, generative AI, retrieval-augmented generation, embeddings, vector search, prompt engineering, and model orchestration frameworks * Implement best practices in LLM-based engineering, including RAG frameworks, evaluation approaches, guardrails, monitoring, and continuous improvement * Develop and apply machine learning, statistical modelling, and mathematical optimization techniques to support predictive decision-making, scenario analysis, resour

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