National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Analyst - Portfolio Risk and Analytics

Infosys BPM
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Requirements/Qualifications:

  • Significant experience with the Bloomberg PORT application.
  • Minimum 3 years' experience with Bloomberg PORT, or similar Fixed Income analytical and performance applications.
  • Expertise in fixed income risk and analytics data and how it is utilized within the investment process.
  • Experience with BONY’s Eagle application and/or Charles River Investment Management System (CRIMS) is a plus including expertise in navigating the Charles River Manager Workbench module.
  • Strong problem solving skills and attention to detail.
  • Effective communication to stakeholders and interpersonal skills.


Responsibilities:

  1. Ensures the integrity of all Risk System related processes to assist the investment team members by producing meaningful, high quality holdings, attribution and characteristic reports for existing and prospective clients.
  2. Acts as front line support for all business users and is the main point of contact for all data issues related to Risk Applications and incorporates feedback from users to expand existing functionality and services.
  3. Assists with the setup and the review of all security types on company's core inventory system and trading systems, ensuring all data is entered accurately to avoid the potential for trade errors or operational loss.
  4. Has a deep mastery of inventory and trading systems such as Eagle, Bloomberg, Charles River Investment Management System.
  5. Collaborates with and assists team members to ensure that security master data in the trading and inventory systems is consistent with the data in the risk systems on a daily basis.
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.