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Data Scientist
5 months ago
Location: Downtown Toronto – Hybrid
Duration: 6 months
What We Are Looking For
As a Data Scientist with expertise in Machine Learning, and advanced analytics you will play a crucial role in advancing our data-driven strategies and optimizing investment performance. You will collaborate with cross-functional teams to analyze internal and market data, assess algorithms, curate training datasets, and construct data pipelines, ML engineering, and data visualizations. We are looking for someone passionate about using a mix of rigorous analysis, market and product data, empathy and intuition to deliver on projects that will transform the decision-making capabilities. This is a high impact role that is well suited to an entrepreneurial, highly collaborative person who is excited by the challenge of identifying opportunities, validating data, building and testing hypotheses, and delivering valuable insights.
Your Responsibilities
- Utilize statistical techniques and predictive modeling to forecast market trends, risk factors, and investment opportunities.
- Conduct comprehensive analysis of marketplace of AI models and determine buy vs build decisions.
- Design, develop, and implement advanced machine learning algorithms to enhance investment strategies and decision-making processes.
- Collaborate with portfolio managers, analysts, and other stakeholders to understand business requirements and translate them into actionable insights.
- Evaluate model performance through rigorous testing and validation, ensuring accuracy, reliability, and scalability.
- Stay abreast of industry trends, emerging technologies, and best practices in data science and AI, providing recommendations for continuous improvement.
- Communicate complex technical concepts and findings to non-technical stakeholders in a clear and concise manner.
- Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field; advanced degree preferred.
- 5+ years of experience in data science, with a focus on AI model analysis and training in a financial or asset management setting.
- Proficiency in programming languages such as Python, R, or Java
- Hands-on experience in machine learning libraries is a bonus (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of statistical analysis, quantitative research methodologies, and predictive modeling techniques.
- Demonstrated experience in evaluating and optimizing AI models for performance, accuracy, and scalability.
- Excellent problem-solving skills with the ability to think critically and creatively in a fast-paced environment.
- Effective communication and collaboration skills, with the ability to work cross-functionally and influence key stakeholders.
- Experience with MLOps
- Experience with Microsoft: Azure, Purview, OpenAI service, etc
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