Lead Analyst: Supply Chain SME

Fitch Ratings
London
6 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist, Inventory Management

Data Analyst

Data Analyst

Data Admin Specialist / Data Analyst

Software Engineer

Supply Chain Analyst SME

BMI is currently seeking a highly skilled Supply Chain Analyst SME to drive our new AI-driven Supply Chain Data & Analytics products.

Our new Supply Chain Data & Analytics product – which leverages AI to quantify and track country level risks - delivers unique, significant value to our diverse user base across financial services, corporates, and government.

What We Offer:

The opportunity to lead the development of a high value product, which forms a core part of BMI’s emerging Risk Analytics strategy Close engagement with BMI’s customer base, and the opportunity to act as a Thought Leader on Supply Chain issues A fast-paced and supportive working environment in which innovation is backed and individuals can thrive.

We’ll Count on You To:

Take ownership of BMI’s country level Supply Chain Data & Analytics product Develop and maintain deep understanding of the Supply Chain industry and trends Collaborate with BMI’s Data Scientists to conceptualise and develop models to quantity Supply Chain risks, and identify key data sources to help measure risk Work with a team of analysts in training / validating the AI model, and mentor the team to drive performance and engagement Be a key point of contact for customers, understanding their needs and positioning our Supply Chain solution to their business challenges Take ownership of the Supply Chain GTM, coordinating with internal and external stakeholders Write and publish thought leadership, and communicate it to BMI’s subscription and Advisory customers, as well as in public forums

What You Need to Have:

Your relevant experience and ability to demonstrate the attributes and skills we require are more important than specific educational qualifications. However, academic qualifications in areas such as Supply Chain Management, Business Administration, Economics or Data Science may be beneficial Minimum 10yrs experience in operational or analytical role covering Supply Chains, translating into proven expertise in supply chain industry trends, market analysis, and risk assessment Strong client-facing skills with the ability to build and maintain relationships.  Exceptional written and verbal communication skills Experience in writing thought leadership content and presenting at industry events Demonstrated ability to train and mentor junior staff

What Would Make You Stand Out:

Familiarity with AI / ML techniques, with experience in model development Proficiency in data analytics tools and programming languages Strong analytical and problem-solving skills Ability to work effectively in a fast-paced, dynamic environment

Why Fitch?

At Fitch Group, the combined power of our global perspectives is what differentiates us. Our global network of colleagues comes together to accomplish things greater than they ever could alone.

Every team member is essential to our business and each perspective is critical to our success. We embrace a diverse culture that encourages a free exchange of ideas, guaranteeing your voice will be heard and your work will have an impact, regardless of seniority.

We are building incredible things at Fitch and we invite you to join us on our journey.

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.