Data Science Developer - Permanent - Cfa Level 1 - London

As a Data Science Developer specialising in Machine Learning & Deep Learning, you will play a crucial role in our dynamic Portfolio Performance Analytics team. In this position, you will be at the forefront of leveraging advanced quantitative techniques to enhance decision-making processes for Private Credit, Liquid Credit, and Private Equity Fund of Funds products Investment Products.

Key Responsibilities

1. Model Development and Enhancement:
   • Utilise your expertise in machine learning and deep learning to develop and refine quantitative models, such as credit risk models and alpha models, for risk assessment, portfolio optimisation, and alpha generation.
   • Collaborate with cross-functional teams to integrate advanced quantitative techniques into the investment process and corporate fund finance operations.
2. Data Analysis and Integration:
   • Conduct thorough business analysis to identify potential risks and opportunities associated with investment decisions.
   • Collaborate with business stakeholders to understand their goals and provide quantitative insights that align with overall business strategies.
   • Work with large datasets, utilising statistical methods and machine learning algorithms to extract meaningful insights that inform investment decisions.
3. Risk Management:
   • Contribute to a well-rounded approach to managing risks across our diverse alternative investment products, corporate fund finance, and treasury management.
   • Monitor and assess the risk exposures of the portfolios, identifying potential areas for improvement and mitigation.
4. Quantitative Research:
   • Stay abreast of industry trends and advancements in quantitative finance, machine learning, and deep learning, and apply this knowledge to enhance the firm's quantitative capabilities.
   • Conduct thorough research on market trends, investment strategies, and relevant financial instruments.
5. Model Delivery Cycle:
   • Manage and enhance the model delivery cycle, ensuring timely and effective deployment of quantitative models into the investment process.
   • Work closely with the technology teams to integrate innovative models into the investment decision-making framework.
6. Performance Monitoring:
   • Implement robust performance monitoring processes to track and evaluate the effectiveness of quantitative models and investment strategies.
   • Provide regular reports and analysis on the performance of portfolios, identifying areas for improvement and optimisation.
7. Collaboration and Communication:
   • Collaborate with portfolio managers, corporate finance managers, business development managers, and other stakeholders to understand their needs and provide quantitative solutions.
   • Clearly communicate complex quantitative concepts and findings to non-technical stakeholders, fostering a collaborative and informed decision-making environment.

Required Qualification/Skills

1. Educational Background:
* Master's in a quantitative discipline such as Computer Science, Finance, Economics, Statistics, or a related field (preferred).

2. Professional Experience:
* Minimum of 3-5 years of experience in quantitative analysis, financial modelling, and software development.
* Demonstrated experience in developing quantitative models for portfolio optimisation, risk management, and performance attribution.

3. Financial Expertise:
* Passed CFA Level - 1.
* Strong understanding of financial markets, investment products, and risk management concepts.
* Experience in working with financial data, analysing balance sheets, cash flows, and financial statements.