Company Overview
We are a boutique financial services firm providing unbiased expertise, tailored financial solutions and best-in-breed technology to clients around the world. We are seasoned experts across the full suite of wealth management, multi-family office, asset management and corporate advisory services. Through our open architecture model, we ensure you benefit from the combination of institutional rigor and bespoke solutions.
Role Overview
We are seeking a skilled Data Scientist with at least 3 years of experience in dealing with large financial data sets to support development of portfolio solutions. This role will leverage machine learning and statistical modelling techniques to enhance our investment strategies, risk assessment, and portfolio performance.
Key Responsibilities
- Develop, implement, and maintain quantitative models for various portfolio solutions, including: (a) development of structured solutions such as single stock volatility strategies, (b) portfolio optimization techniques through the use of various overlays (c) quantitative research across macro and equity asset classes (d) and other advanced analytics initiatives to process increasing firm-wide data
- Apply machine learning techniques to generate predictive insights (starting with 3 specific models)
- Perform feature engineering, model tuning, and validation to ensure robustness and performance
- Analyze large, multi-source financial datasets to identify trends and risk drivers
- Support trading and investment teams with data-driven insights and analytical tools
- Collaborate with cross-functional teams to translate business requirements into scalable technical solutions
- Ensure model accuracy through rigorous testing and ongoing performance monitoring
- Overtime model training/refinement will be required
Qualifications
- Master's degree in Financial Engineering, Mathematical Finance, Data Science, Statistics, or a related quantitative discipline
- At least 3 years of professional experience finance in data science or quantitative research, preferably within asset management, banking, or investment firms
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn; experience with TensorFlow or PyTorch is a plus)
- Though most of the work is expected to involve structured data sets, experience with unstructured data sets is a plus
- Understanding of the pros/cons of various machine learning techniques
