Data Scientist

Overview

We are seeking a talented and driven Data Scientist to join our team. The 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. This role contributes to overall data science capabilities at OTPP and supports data science practices and capability development.

Responsibilities

• Actively participate in the end‑to‑end machine learning and AI development lifecycle, from experimentation and prototyping through 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 optimisation 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 optimisation‑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, optimisation 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, 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 optimisation‑based solutions.
• Support the delivery of key reports, analytics, models, visualisations, prototypes and decision‑support tools aligned with business priorities.
• Continuously identify opportunities to enhance AI/ML and optimisation approaches, leveraging new techniques, emerging tools and alternative data sources.

Qualifications

• Bachelor’s degree in a quantitative discipline. Master’s or Ph.D. in a quantitative discipline with a focus on data science, statistical modelling, machine learning, AI, optimisation or computer science is preferred.
• Experience in machine learning, data science, AI engineering or applied analytics in industry or academia.
• Experience in mathematical and statistical model development to support predictive decision‑making.
• Strong familiarity with large language models, generative AI, retrieval‑augmented generation, embeddings, vector databases, prompt engineering and LLM evaluation.
• Strong familiarity with mathematical optimisation techniques such as linear programming, mixed‑integer programming, nonlinear optimisation, stochastic optimisation, simulation‑based optimisation or heuristic methods.
• Ability to formulate business problems as analytical, machine‑learning, AI or optimisation problems, including defining objectives, constraints, trade‑offs and success measures.
• Proficient programming skills in Python, R, Spark or other open‑source languages and related libraries.
• Experience with relevant data science, machine‑learning, AI or optimisation libraries and tools such as scikit‑learn, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, OR‑Tools, Pyomo, Gurobi, CPLEX, CVXPY or similar.
• Proficient SQL skills for mining complex and multi‑source data environments.
• Experience in both on‑premise and cloud computing environments.
• Experience analysing large sets of data for patterns and correlations using visualisation tools.
• Proficient with Git workflow and good coding habits including documentation, version control, testing, reproducibility and code review.
• Passionate about applying analytics, AI, machine learning and optimisation 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 and teamwork orientation.
• Previous experience in investments, capital markets, private equity or private markets is an asset.

Benefits

• Pay‑for‑performance with a base salary range of $105,000 to $155,000 and annual incentive based on individual and enterprise performance.
• Comprehensive employer‑paid benefits coverage.
• Retirement income through a defined benefit pension plan.
• Opportunity to invest back into the fund through the Deferred Incentive Program.
• Flexible work environment combining in‑office collaboration and remote working.
• Competitive time off.
• Flexible Travel Program giving you the option to work abroad for up to a month each year.
• Employee discount programs.