Head of Investment Finance Analytics

Cramond Bridge
2 weeks ago
Applications closed

Related Jobs

View all jobs

Strategic Finance & Insights Analyst

Head of Development - Fintech SaaS. Full Remote

Head of Development - Fintech SaaS. Full Remote

Head of Development - Fintech SaaS. Full Remote

Senior Microsoft SQL Developer - Fintech SaaS. Full Remote

Senior Microsoft SQL Developer - Fintech SaaS. Full Remote

Join us as Head of Investment Finance Analytics

This high profile role will see you influencing decisions through the provision of commercial and financial expertise, insight and analytics for the enterprise wide investment portfolio

We’ll look to you to drive value add insight on the investment portfolio from financials to performance insights and allocations, while creating efficiencies in how we operate and improving the service offering to our stakeholders

You can expect great exposure as you build strong relationships and work closely with key stakeholders and business partners across the bank

What you'll do

As Head of Investment Finance Analytics, you’ll be working with stakeholders and business partners to identify and define opportunities for cost efficiencies across the investment portfolio. 

You’ll be driving value add insight and analytics to support decision making, building scenario models to proactively manage the investment cost shape, and challenging data to make sure that the right investment prioritisation decisions are made.
 

Your key priorities will include:

Leading a Business Intelligence team to provide financial and non-financial information to support business partnering activity and customer needs

Developing the team to provide analyst support and actionable insight to the business that can drive discussions and decisions

Managing the end-to-end delivery of requested financial projects and analysis

Engaging with the business to define requirements and agree deliverables, including strategy, cost management, pricing and business development

Supporting business partners and senior audiences in the management of cost base and business performance management

The skills you'll need

We’re looking for a finance professional with significant experience, and strong business intelligence skills with the ability to assimilate information and formulate solutions. Additionally, you’ll need to hold a CA, ACA, CIMA or MBA qualification or equivalent.

You’ll also bring:

Strong commercial awareness and business acumen

Strong technical knowledge of budgeting, forecasting and modelling

Excellent stakeholder management skills, with the ability to build and influence relationships

Excellent communication skills, with the ability to communicate complex financial information in a concise, non-technical manner

Proven leadership skills

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.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 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.