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.
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.
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, resource allocation, portfolio construction, and other complex business problems
Translate business objectives, constraints, and trade-offs into analytical, AI/ML, or optimization-based solution approaches
Champion strong coding standards, including documentation, version control, testing, reproducibility, and code review practices
Contribute to building and promoting best practices across the team by sharing knowledge, reusable patterns, and lessons learned
Stay up to date with emerging technologies, industry trends, and advancements in AI, machine learning, optimization, and data science
Explore and experiment with new techniques, tools, models, and data sources, providing thoughtful recommendations to the business
Collaborate with team members on research, analysis, experimentation, and idea generation, while progressively developing independent insights
Build strong partnerships with business stakeholders, particularly within Private Markets, to drive impactful data-driven, AI-enabled, and optimization-based solutions
Support the delivery of key reports, analytics, models, visualizations, prototypes, and decision-support tools aligned with business priorities.
Continuously identify opportunities to enhance AI/ML and optimization approaches, leveraging new techniques, emerging tools, and alternative data sources
Bachelor’s degree in a quantitative discipline.
Master’s or Ph.D. degree in a quantitative discipline with a data science, statistical modelling, machine learning, AI, optimization, or computer science focus preferred.
Machine learning, data science, AI engineering, or applied analytics experience in industry or an academic setting.
Experience in mathematical and statistical model development to support predictive decision-making
Experience or strong familiarity with large language models, generative AI, retrieval-augmented generation, embeddings, vector databases, prompt engineering, and LLM evaluation
Experience or strong familiarity with mathematical optimization techniques, such as linear programming, mixed-integer programming, nonlinear optimization, stochastic optimization, simulation-based optimization, or heuristic methods is a huge asset
Experience formulating business problems as analytical, machine learning, AI, or optimization problems, including defining objectives, constraints, trade-offs, and success measures
Proficient programming skills in Python, R, Spark, or other open-source programming languages and related libraries
Experience with relevant data science, machine learning, AI, or optimization libraries and tools, such as scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, OR-Tools, Pyomo, Gurobi, CPLEX, CVXPY, SciPy, or similar
Proficient SQL skills in mining complex and multi-sourced data environments
Experience in both on-premise and cloud computing environments
Experience analyzing large sets of data for patterns and correlations using visualization tools
Proficient with Git workflow
Good coding habits, including documentation, version control, testing, reproducibility, and code review
Passionate about applying analytics, AI, machine learning, and optimization in the investment area
Ability to quickly learn and adopt new technologies, tools, and approaches
Ability to independently research potential solutions from industry, open-source, vendor, and academic resources
Ability to articulate thoughts and ideas to effectively collaborate with business, data, and technology partners
Strong problem-solving skills working in a team-based environment
Previous experience in investments, capital markets, private equity, or private markets is an asset.
