Valuation Controller - Emerging Markets Rates

TN United Kingdom
London
1 month ago
Applications closed

Related Jobs

View all jobs

Lead Data Consultant

Risk Data Scientist

Data Analyst

Powertrain Charging Test Data Engineer

Data Scientist - Remote

Flight Software Engineer - Space

Social network you want to login/join with:

Are you the right applicant for this opportunity Find out by reading through the role overview below.Valuation Controller - Emerging Markets Rates, London Client:Location: London, United KingdomJob Category: FinanceEU work permit required:

YesJob Reference: 6379847d4631Job Views: 95Posted: 11.03.2025Expiry Date: 25.04.2025Job Description: If you are looking for a role in the Valuation Control Group Emerging Markets team, you are in the right place!Valuation Control Group covers a broad range of products across the entire liquidity spectrum. With core valuation processes largely delivered through dedicated technology and quantitative research resources, the team focuses on insightful analysis leveraging multiple market data sources through advanced analytics platforms.As a Vice President of Corporate Controller within the Valuation Control Group Emerging Markets team, you will oversee all elements of the valuation control framework for the Europe, Middle East, Africa, and Latin America non-linear portfolios. This includes independent price verification, valuation and prudent valuation adjustments, stress valuation adjustments, and fair value measurement. Your work will encompass a broad range of Interest Rates products, with a primary focus on Interest Rates Volatility Products. If you possess a solid understanding and keen interest in financial markets, coupled with robust analytical skills and a readiness to contribute as part of a high-performing team, we encourage you to apply.Job ResponsibilitiesBe responsible for all aspects of the valuation control framework for the EMEA and LATAM non-linear portfolios, including independent price verification, valuation and prudent valuation adjustments, valuation adjustments stress and fair value measurement.Review complex transactions associated with the Emerging Markets business, challenging the trading business to ensure appropriate constraints/controls in place.Identify emerging valuation risks and drive methodology enhancements to ensure valuation controls accurately capture market dynamics and opportunities to enhance control efficiency.Partner with Quantitative Research and Model Review Groups to assess limitations in trading models and implement compensating controls and model limitation adjustments.Own the relationship with Front Office and key Finance, Technology and Risk partners providing value-add analysis on month-end results, illiquid and concentrated valuation positions, revenue from new deals and complex transactions and new products.Partner and participate in projects within the group and the wider Finance organization together with Front Office, Quality Reporting and Technology and participate in regulatory exams and address bank’s regulators inquiries.Required Qualifications, Capabilities, and Skills7+ years of experience in financial industry or relevant experience.Interest Rates markets and products experience is mandatory.Must have quantitative aptitude and keen interest in financial markets and products. Keen interest in developing and coaching a diverse team a must.Critical thinker with sound judgement and ability to challenge constructively.Curious personality; inclusive; detail-oriented; always looking to improve.Strong communication skills and ability to synthesize complex subjects; good at multi-tasking and prioritization.Basic Microsoft Office & strong Excel skills are required.Preferred Qualifications, Capabilities, and SkillsUnderstanding of or training in financial products or derivatives pricing preferred.Knowledge of data science (Machine learning), analytics platform (Alteryx) and data visualization tool (Tableau) will be advantageous.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.