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