Description:
The Principle Data Scientist is a significant contributor to OTPP’s AI practices and overall AI capabilities.
Who You'll Work With
The Principal Data Scientist will report to Director, Data Science & Advanced Analytics. You'll join the Data, Analytics & AI team, a multidisciplinary group of data scientists, data analytics specialists, data engineers, and data visualization experts. Collaborating closely in this environment, you'll support the development of Generative AI applications and the delivery & management of Analytical & AI technologies. You’ll also work directly with our Middleware & Product engineering team, Product Owners, Enterprise Architects, Software developers, and internal business team clients (Capital Markets, Quants, Private Investment, and more).
What You'll Do
- Lead the design, development, and implementation of AI models and algorithms to support investment decisions, risk management and operation efficiency initiatives.
- Analyze large, complex structured/un-structured datasets to uncover patterns, trends, and potential opportunities.
- Collaborate with various teams to integrate data science solutions into investment workflows and decision-making processes.
- Develop and deploy scalable, production-ready models and ensure their robustness, accuracy, and compliance with regulatory standards.
- Drive innovation by researching and applying the latest advances in AI, machine learning, natural language processing, and statistical modeling relevant to the organization.
- Mentor and provide technical guidance to junior data scientists and ML engineers.
- Communicate complex analytical concepts and results clearly to both technical and non-technical stakeholders, including senior management.
- Ensure adherence to data/AI governance, privacy, and ethical standards in all data science initiatives.
- Contribute to the firm’s data and AI strategy and help identify new data sources and technologies to enhance AI capabilities.
- Independent analysis approach based on business context.
What You'll Need
- Master’s or PhD degree in Computer Science, Statistics, Mathematics, Financial Engineering, or a related quantitative discipline.
- 7+ years of experience in data science, quantitative research, or machine learning.
- Passionate about leveraging data science in investment and asset management
- Deep expertise in statistical modeling, machine learning, time series analysis, and predictive analytics.
- Experience with Gen-AI/Agentic AI application development
- Strong programming skills in Python, R, SQL, and experience with Cloud computing
- Experience with current MLOps practices and implementation
- Experience with investments, risk management frameworks, and investment processes is an asset.
- Proficient SQL skill in mining complex and multi-sourced data environment
- Ability to quickly learn/adopt to new technology and approaches
- Ability to independently research on potential solutions from both industry and academic resources
- Excellent problem-solving skills and ability to work independently on complex projects.
- Strong communication skills with the ability to explain technical concepts to diverse audiences.
- Foundational Knowledge in NLP: understanding of basic NLP concepts such as tokenization, large language model architectures, LLM fine-tuning.
- Statistical and Machine Learning Knowledge: familiarity with foundations of machine learning, e.g. elementary statistics and probability, linear algebra, regression and classification tasks, supervised and unsupervised learning, neural networks and deep learning, model architectures and training.
- Experimental Design and Evaluation: knowledge of designing experiments, including splitting data into training and testing sets, cross-validation, and evaluating model performance using metrics like precision, recall, etc.
- Familiarity with Time Series Analysis: understanding of time series data, especially in the context of financial data, and the ability to integrate NLP outputs with time series models
- Strong knowledge of new AI technologies and industry trends (commercial software and open-sourced solutions).
- Experience in industry or an academic setting of:
- Experience with application development using Generative AI principles (e.g., prompt engineering), RAG, finetuning, Agentic AI etc …
- Hands-on experience with AIOps, from AI application development to deployment to governance.
- Strong background in data warehousing, ETL, and data modeling
- Proficiency in SQL or similar query languages for data exploration and troubleshooting
- Expertise in public cloud platforms (Azure, AWS, GCP)
- Hands-on experience with cloud computing architectures
- Hands-on experience with version control (e.g., Git) and CI/CD pipelines
- Experience working in Agile environments.
What We’re Offering
- Pay-for-performance environment that offers competitive salary and incentive
- Numerous opportunities for professional growth and development
- Comprehensive employer paid benefits coverage
- Retirement income through a defined benefit pension plan
- The opportunity to invest back into the fund through our Deferred Incentive Program
- A flexible/hybrid work environment combining in office collaboration and remote working
- Competitive time off
- Our Flexible Travel Program gives you the option to work abroad in another region/country for up to a month each year
- Employee discount programs including Edvantage and Perkopolis