Data Scientist

About the role

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.

Responsibilities

• 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

Requirements

• 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 workf

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Company Intel

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