Investment Risk Analyst

Selby Jennings
London
1 year ago
Applications closed

Related Jobs

View all jobs

Portfolio Revenue & Debt Data Analyst - Swindon, Wiltshire

Alpha Data Services, Performance Ready Data Analyst, EMEA Lead, Vice President

Data Engineer

Data Engineer

Portfolio Revenue & Debt Data Scientist

Portfolio Revenue & Debt Data Scientist

Job Title: Investment Risk Analyst Location: LondonEmployment Type: Full-Time About the Role: Our clients are seekingan Investment Risk Analyst to join their team and support theirportfolio and risk management strategies. The ideal candidate willhave a keen understanding of financial markets, risk managementframeworks, and a strong analytical background. This role focuseson identifying, assessing, and mitigating potential risks in theirinvestment portfolios, contributing to strategic decision-makingand helping ensure the long-term success and stability of theirclients' assets. Key Responsibilities: - Risk Assessment: Conductin-depth analysis of financial market trends and macroeconomicindicators to identify risk factors that may impact the company'sinvestment portfolios. - Data Analysis: Analyse large datasets toassess exposure, volatility, credit, market, and operational risksacross different investment products. - Portfolio ManagementSupport: Collaborate with portfolio managers to understand riskexposures within portfolios and recommend adjustments based oncurrent market conditions. - Model Development and Validation:Develop and validate risk models (e.g., Value-at-Risk, stresstesting, scenario analysis) to quantify risk exposures and simulatevarious economic scenarios. - Reporting: Prepare regular and ad hocrisk reports, clearly communicating findings to investment teams,senior management, and stakeholders. Preferred Qualifications: -Bachelor's degree in Finance, Economics, Mathematics, or a relatedfield; Master's degree or CFA/FRM certification preferred. - 4+years of experience in investment risk analysis, financial riskmanagement, or a related field. - Strong proficiency in statisticalanalysis tools and programming languages such as Python, R, SQL, orMATLAB. - Familiarity with financial instruments and derivatives,as well as risk metrics such as VaR, CVaR, and expectedshortfall.

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.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.