Finance Function Transformation Consulting Managers – Insurance

S.I.S Executive
Newcastle upon Tyne
1 month ago
Applications closed

Related Jobs

View all jobs

Data & Insights Analyst

Head of Commercial Analysis and Reporting

Data Engineer

Data Engineering Lead - Finance and Master

Data Analyst – Motorsport

Data Analyst – Motorsport

Position : Finance Function Transformation Managers – Insurance


Industry : Management Consulting


Vertical : Financial Services – Insurance


Location : UK Wide – Remote Working


Package : Basic Salary up to £100K plus significant bonus and benefits package


Background


Our client is a highly regarded, well respected listed Global consulting firm form focussed on transformational consulting into the Financial Services Sector. The business has experienced considerable growth year on year over the last 2 decades, through acquisition, service and client proposition development and a reputation for best-in-class client delivery. They are currently looking to develop and expand their consulting proposition within the UK & European Insurance market and are looking for a number of highly talented Insurance specialists at varying levels to join the business with particular focus and expertise in Finance Function Transformation. The business operates with a 1 team philosophy with regards to consulting engagements and as such is naturally collaborative in nature. Culturally the business is non-political with an energised and diverse workforce who demonstrate a client centric can-do attitude. Joining the business, you can expect an excellent compensation package including a bonus which has paid out consistently over the last decade, a true hybrid working model and career progression opportunities based on individual merit


The Roles


These are classic client facing C-suite (CFO) Insurance Sector consulting roles covering Life, Non-Life & Speciality , where you will be working as part of a Finance Transformation team running large scale projects, programs and client workshops: leading, coaching and mentoring teams of junior consultants at varying levels of experience as well as guiding the incumbent client Finance teams through the change and Transformation program. The Transformation practice can be best described as Technology enabled consulting and covers both strategy and implementation in the areas of Regulatory change compliance such as IFRS 17 as well as broader Finance Function change such as : Finance Target Operating Model Design, Improvements in accuracy and cost optimisation across P2P, R2R, O2C, FP&A, Systems Architecture, Chart of Accounts, General Ledger, Data Analytics.


The Candidates


As mentioned we are looking for a number of Managers for the business. Your experience will have been gained from within another global consulting organisation (operating currently at Manager or equivalent) focused on Finance Transformation within the Insurance sector. In order to be successful, you will need a working knowledge of the key technologies and systems involved in insurance finance including Cloud Technology, Actuarial models, ERP systems, Consolidation tools, Reporting/Analysis tools and data platforms as well as a full awareness and understanding of Insurance reporting standards, requirements and compliance. On a broader level it is expected you have knowledge of Insurance Finance including leading practice reporting processes, controls, and risks in addition to knowledge and understanding of key technology trends in Insurance including migration to Cloud, SaaS, Automation, Big Data. It is expected you have a working knowledge of the end-to-end finance systems architecture, how each of the components are linked and technologies which are available in the market and with this a demonstrable ability to design the strategic finance systems architecture required given client requirements and build the transition states and roadmaps required. As an individual you need to be very much a natural self-starter, a pro-active team player who is genuinely passionate about building high performance teams and experienced in working in a multi-disciplined environment.


Please be rest assured of discretion and confidentiality and all contact is in line with GDPR. S.I.S Executive is a Global Executive Search organisation acting on behalf of a third-party client

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.