Risk Data Officer

Manchester
2 weeks ago
Applications closed

Related Jobs

View all jobs

Risk Data Governance- BCBS239

Risk Data Engineer - C#- Tech-Driven Global Hedge Fund

Senior Privacy Associate

Senior Privacy Associate

Security Consultant, Information Security

Interim Lead Product Manager

Join us as a Risk Data Officer

In this key role, you’ll be supporting Risk MI and reporting activities

We’ll look to you to provide data analysis and data quality issue investigation support

It’s an opportunity to hone your skills as you assist in providing expert oversight to bank-wide programmes 

We offer a hybrid way of working where you’ll be based in our Manchester office for a minimum of two days per week, with the rest of your time working from home

What you'll do

As a Risk Data Officer, you’ll be helping to improve data quality across the risk domains, including providing expert input into root cause analysis and remediation projects on behalf of Risk Data.

As well as this, you’ll be:

Ensuring consistency, accuracy and timeliness of data and reporting used for insightful analysis to support board, senior risk and risk appetite committees

Assisting with providing expert support to Risk in respect of MI, risk reporting and data governance activities

Providing ongoing monitoring of our risk metrics, investigating results and identifying areas for remediation

The skills you'll need

We’re looking for someone with a willingness to learn about data management and relevant Cloud technologies such as AWS or GCP, coupled with data interrogation, analytical and presentation skills. You’ll also need experience of GUI platforms like Tableau and Power BI, or have the ability to develop these skills. You’ll be a self-starter with a willingness to make continuous improvements to business processes.  

You’ll also demonstrate:

Good communication and stakeholder management skills, along with the willingness to learn how to engage and influence to build strong working relationships

Excellent attention to detail and the ability to present information effectively up to management level

Good planning and organisational skills, with the ability to handle multiple and varied tasks simultaneously

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.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.