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Hayfin Capital Management
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  • This role is based in the London office on the European HYSL Team, rep... Read More
    This role is based in the London office on the European HYSL Team, reporting to the Head of European HYSL. The Trade Assistant will work closely with Portfolio Managers and Traders, as well as collaborate with the Operations team and other support functions.Responsibilities Support day-to-day HYSL Portfolio Management and Trading functions; collaborate with Operations and other supporting functions; act as a key liaison between front and middle office Manage order, trade booking and reconciliation processes Timely and accurate logging of trades, and adherence to trading policies and procedures Run hypothetical trade compliance testing for Collateralised Loan Obligations and, where applicable, mandate limitations/restriction testing for other portfolios Responsible for coordination of trade recaps, allocations and supporting rationale (including back-up records and verifications), maintaining outstanding orders Ensure accuracy across all processes and systems Prepare and maintain various reports including P&Ls, market summary sheets, outstanding orders and primary deal pipeline Provide oversight of portfolio and trading data quality, including identifying and resolving data issues, whilst implementing risk controls Ensure compliance and due diligence measures are adhered to in accordance with firm policies and regulatory requirements Liaise with Sell-side Broker/Dealers and Administrative Agents to obtain asset information, trade details, expedite settlements, data-site access and other ad hoc requests RequirementsEssential 1-3 years’ experience on the buyside or sell side - ideally in a Middle Office / Operations function in fixed income (high yield) or leverage loans Strong attention to detail Ability to act with a sense of urgency and thrive in a fast-paced environment whilst also delivering consistently and accurately Ability to identify and respond quickly to discrepancies in data sets and resolve Adaptability, problem-solving and communication skills PreferredFamiliarity with coding (Advanced Excel/ Python or similar) and/or data visualisation tools (Power BI, Tableau or similar) Read Less
  • IT Data Engineer  

    - London
    About The RoleThe IT Data Engineer works within the IT department to u... Read More
    About The RoleThe IT Data Engineer works within the IT department to undertake analysis, design software and data solutions and solutions aimed at improving our business processes, decision making capabilities and analytic workflows.This position will be part of a small team tasked with producing high quality, innovative solutions to enhance our core business systems and create significant intellectual property that will differentiate us in our sector and markets. The position holder will also be instrumental in helping establish leading software and service delivery processes and steer the team in the direction of DevOps, continuous integration, continuous delivery and delivery lifecycle automation.This is a role for a sector specialist who has experience working as an analyst programmer in a fast-paced environment and also for someone who is friendly, approachable and proactive in bringing new ideas to the table.ResponsibilitiesBusiness Analysis Perform business analysis in support of business change, project delivery or software / database development Evaluate business processes, discover and document requirements, uncover areas for improvement Ensure solutions meet business and technology needs and requirements Document and demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts Perform unit and system acceptance testing against (non) functional requirements Ensure that training services and documentation are in place to educate staff on how to use new software or technology effectively Software Delivery Analyse requirements, design and deliver software and data solutions to meet our goals and objectives as standalone changes or as part of a broader programme of work Review, analyse and test other team members code and solutions where appropriate Contribute to the definition and maintenance of our target state solution architecture, development frameworks and delivery methods Be accountable for the quality of software development and deployment by delivering modular, efficient and testable code Develop software verification plans and quality assurance procedures Delivery Lifecycle Own and maintain the delivery lifecycle for assigned development work Manage 3rd party/external development teams acting as a team lead/scrum master where necessary Review, communicate and work to resolve any impediments or technical challenges encountered whilst developing solutions Contribute to continuous improvement of our software and service delivery by identifying areas of improvement opportunity and taking the initiative to manage the change Management or significant contribution to defining and implementing delivery methods such as DevOps, CI/CD, Test Automation, use of backlogs and sprint planning Champion Service and Support considerations and service transition activity in all development activity Performance & Quality Continually update technical knowledge and skills by attending in-house and external courses, reading manuals and accessing new applications Work with internal and third-party technology teams to ensure development activity is conducted to the expected level of quality and timeliness, providing constructive feedback and coaching where appropriate Effectively manage the balance of time spent developing new solutions versus providing support for incident and problem management Be an ambassador for IT, working across the business to provide effective communication on IT software and service delivery and build relationships with other teams to ensure effective dialogue between departments RequirementsQualities and SkillsCore: Data Engineering: A strong background in data engineering, with thorough understanding of concepts like ETL (Extract, Transform, Load), data cleaning, data structures, and data warehousing. SQL Database Experience: Proficiency in SQL databases with the ability to write complex queries and procedures. Demonstrable experience working with Azure SQL Database and Snowflake are essential to this role. Azure Knowledge: Comprehensive understanding of the Azure platform, including knowledge about its architecture, services, and security measures. Hands-on experience with Azure data services like Azure SQL Database, Azure Data Factory, Azure Data Lake, and Azure Synapse Analytics are essential. Programming Skills: Proficiency in programming languages such as Python, Java, or C#, which are commonly used for data manipulation and automation. Data Modelling: The ability to design and implement effective database models to store and retrieve company data. DevOps Practices: Understanding of DevOps principles and CI/CD pipelines, and experience with tools like Azure DevOps or GitHub. Communication Skills: Ability to communicate effectively with both technical and non-technical stakeholders, understanding their needs and translating them into data solutions. Desired: BI Tools: Experience with BI tools such as Qlik, Tableau or Power BI, for creating reports and data visualizations. Stakeholder Relationship Management: Experience working with different stakeholders, understanding their needs and communicating effectively. Proven ability to maintain strong stakeholder relationships. Big Data Technologies: Familiarity with big data technologies like Apache Spark, Hadoop. Even though they might not be needed directly, the understanding could help in broader data architecture discussions. Unit Testing Frameworks: Experience with unit testing frameworks in languages like Python, Java, or C#. Ability to write and run tests to ensure the integrity of data processes and outputs. Azure Advanced Analytics: Knowledge of Azure's more advanced analytics tools like Azure Analysis Services could be beneficial. Data Lake and Stream Analytics: Even if not a core part of the role, understanding of Azure Data Lake Storage and Azure Stream Analytics could be beneficial in certain scenarios. Data Warehousing: Experience with designing, developing, and maintaining data warehousing systems, even beyond Azure, could be beneficial. Certifications: Possessing Azure Data Engineer Associate certification (DP-200, DP-201) or any other related professional certification can validate your skills and give you an edge. Project Management: Experience with project management methodologies like Agile, Scrum, or Kanban, which can be useful in a team setting. This description reflects the core activities of the role but is not intended to be all-inclusive and other duties within the group/department may be required in addition to changes in the emphasis of duties as required from time to time. There is a requirement for the post holder to recognise this and adopt a flexible approach to work. Job descriptions will be reviewed regularly and where necessary revised in accordance with organisational needs. Any major changes will be discussed with the post holder. Read Less
  • Data Scientist  

    - London
    We are seeking a technically strong Data Scientist to join our Portfol... Read More
    We are seeking a technically strong Data Scientist to join our Portfolio Performance Analytics team. You will play a key role in developing and applying quantitative models that enhance decision-making across Hayfin’s investment strategies. The initial focus will be on Private Credit, where you will support portfolio management, risk assessment, and performance optimization. Over time, there will be opportunities to extend your work across Liquid Credit and Private Equity Fund of Funds strategies.Key Responsibilities1. Quantitative Model Development Design and implement machine learning and statistical models for portfolio analytics, risk evaluation, and alpha generation. Develop robust Python-based pipelines with clear documentation and test coverage. Work cross-functionally with investment, finance, risk, and technology teams to deploy solutions. 2. Data Management & Analysis Analyse large, complex datasets using SQL and Python to support investment research and operational insights. Integrate internal, market, and alternative data sources into modelling frameworks. Conduct exploratory analysis to inform investment decisions and identify signals. 3. Machine Learning & Statistical Techniques Apply supervised and unsupervised learning using frameworks such as JAX (preferred), TensorFlow, or PyTorch. Leverage scientific computing libraries (NumPy, Pandas) and visualization tools (matplotlib/seaborn). Optimize performance with vectorized operations or JIT compilation where appropriate. 4. Financial and Domain Expertise Develop models and tools tailored to private credit investment strategies, including direct lending, special opportunity portfolios. Collaborate closely with the Investment and Risk team to evaluate portfolio exposures, stress scenarios, and downside risk. Support financial analysis across various strategies, including analysis of instruments, financial statements, and risk metrics in the future. 5. Model Delivery & Monitoring Maintain a high-quality model development process including version control (Git), documentation (Sphinx), and testing (pytest). Monitor model performance over time and suggest iterative improvements. Collaborate via workflow tools like JIRA to ensure agile delivery and coordination. RequirementsTechnical Skills Python: Strong programming experience with data science libraries such as NumPy, Pandas, matplotlib/seaborn. SQL: Comfortable querying large datasets and integrating results into Python workflows. Testing & Documentation: Familiarity with tools like pytest and Sphinx. Machine Learning: Hands-on experience with ML frameworks (preferably JAX, or TensorFlow/PyTorch) and core ML concepts. EducationBachelor’s or master’s degree in a quantitative field: Computer Science, Applied Mathematics, Engineering, Physics, or similar.Preferred Qualifications Experience with numerical modelling in a financial or research environment. Exposure to portfolio modelling or analytics in Private Credit. Knowledge of fixed income instruments, credit risk, or portfolio construction principles. Familiarity with Git, JIRA, and collaborative development practices. CFA Level I or equivalent is a plus. Read Less

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Astrid-Lindgren-Weg 12 38229 Salzgitter Germany