Risk Manager – Data Science (Risk Data Science)

Job title:

Risk Manager – Data Science (Risk Data Science)

Company

Nationwide

Job description

A fantastic opportunity has become available as a Risk Manager – Data Science in our thriving Risk Decision & Data Science team (RDDS) – winners of the “Credit Modelling & Risk Team of the Year” at both the 2022 and 2020 Credit Strategy Awards, “Best Use of Technology” at the 2019 Credit Strategy Awards and winners at the Women in Credit Awards for “Rising Star of the Year” (2022 and 2023) and “Team Player of the Year” (2022).The Risk Data Science team are responsible for delivering data science tools and models which are at the heart of decision making for the business, driving great member outcomes. The team apply a wealth of technical experience to develop cutting-edge modelling and data science solutions, ranging from Machine Learning Credit Scoring models to Advanced Outlier Detection Models for identification of criminal behaviour. RDDS is a dynamic and fun place to work, with a strong culture for recognising and rewarding the great work its colleagues do.As a Risk Manager – Data Science, you will be responsible for enabling the delivery of cutting-edge analytical Risk decision tools that optimise decisions across our Retail Lending portfolios (across Application, Behavioural and Collections/Recoveries), Fraud and Financial Crime. You will provide strong technical leadership and support, to lead, motivate and enable your reports and the wider team. You will be engaging senior stakeholders, planning and leading multiple projects relating to the ongoing development and maintenance of data science models across all business areas. The role will require deep understanding of portfolio/member behaviour, different data science techniques, and capability to optimise the use of modelling tools for business decisions. Proven experience in stakeholder management and communication will be integral to the role, as it will involve liaising with 3rd Parties, internal IT, Data and Systems SMEs to drive forward these data science initiatives to delivery. Your role will also be critical to ensure colleagues can develop their careers and continue to make RDDS a great place to work.At Nationwide we offer hybrid working wherever possible. More rewarding relationships are supported through our hybrid approach, bringing colleagues together across our UK wide estate, whilst also supporting generous access to home working. We value our time in the office to solve problems, to learn, and to feel connected.For this job you’ll spend at least two days per week, or if part time you’ll spend 40% of your working time, based at our Swindon office to best lead others, and for training, technical workshops and wider team activities. If your application is successful, your hiring manager will provide further details on how this works. You can also find out more about our approach to .If we receive a high volume of relevant applications, we may close the advert earlier than the advertised date, so please apply as soon as you can.What you’ll be doingYour responsibilities will include:

• Developing, documenting and delivering cutting-edge Machine Learning and Data Science models, employing relevant statistical techniques.
• Effectively plan and prioritise activities, engaging key stakeholders across the business.
• Working with stakeholders to deliver and provide expert opinions on the best modelling solutions, from build stages through to safe implementation.
• Ensuring all Data Science model developments are high quality and adherent to modelling standards and validation governance.
• Line management, training, coaching and mentoring less experienced team members in the application and best practise of Data Science modelling.
• Managing and providing technical leadership to a team, creating a working environment to promote a fantastic team culture alongside high-performance.
• Communicating model performance to risk committees and senior management.

The role will involve engagement with the Systems, Product Risk, Financial Crime, Collections, Recoveries, Retail IRB Modelling & Model Validation teams to ensure that requirements are understood, met and implementable. You will also be responsible for presenting your projects and insights to the relevant modelling fora and business committees.About youTo be successful in this role you will have:

• Demonstrable experience in delivering innovative and creative Data Science solutions to address complex business problems, using coding in Python/R/SAS, or similar.
• Deep knowledge of different Data Science techniques, such as Gradient Boosting, Random Forests, Neural Networks, Support Vector Machines, unsupervised learning methodologies etc., including their merits and limitations.
• Hands-on experience of leading, motivating and mentoring colleagues to deliver advanced analytical tools for the business.
• Strong knowledge of Economic Crime and Credit Risk models.
• A proven track record of senior stakeholder management, with high quality communication and influencing skills.
• A PhD, MSc or strong quantitative degree ideally from a Mathematics, Statistics, Computer Science or related subject.

Our Customer First behaviours are all about putting customers and members at the heart of how we work together. You can strengthen your application by showing the behaviours that resonate with you, and how you might have already demonstrated these.

• Say it straight – This is about being honest and direct with good intent and saying what needs to be said in the room. It’s also about being clear, precise, and using language that we and, importantly, our customers and members can understand.
• Push for better – This is about aiming high and constantly looking for better in how we work together and serve our customers and members.
• Get it done – This is about prioritising what will have the greatest impact, being decisive and taking accountability for delivering on the end-to-end outcome.

We know applying for jobs can sometimes feel like you’re sending an application into a black hole. We review each application individually. So, it’s a good idea to call out your most relevant experience on your application to give yourself the best chance.The extras you’ll getThere are all sorts of employee benefits available at Nationwide, including:

• A personal pension – if you put in 7% of your salary, we’ll top up by a further 16%
• Up to 2 days of paid volunteering a year
• Life assurance worth 8x your salary
• A great selection of additional benefits through our salary sacrifice scheme
• Access to an annual performance related bonus
• Access to training to help you develop and progress your career.
• Wellhub – Access to a range of free and paid options for health and wellness.
• 25 days holiday, pro rata

What makes us differentNationwide is the world’s largest building society. With over 15 million customers, we have a relationship with almost a quarter of the UK’s population. We’ve got the scale to compete with the big banks, but we’re not a bank.As a building society, we’re owned by our members – that’s our customers who have their current account, mortgage or savings with us. It means we can do things differently to deliver our Purpose – Banking – but fairer, more rewarding, and for the good of society.When you work at Nationwide, you can experience that difference for yourself. You’ll be part of a high-performing, purpose-driven organisation that offers rewarding career experiences and a highly competitive range of benefits to match. You’ll also be joining us at an important time as we seek to reach more and more people in the UK. We want everyone in the UK to know that they don’t have to bank with a bank. They can choose a modern mutual instead.What to do nextIf this role is for you, please click the ‘Apply Now’ button. You’ll need to attach your up-to-date CV and answer a few quick questions for us.We respond to everyone, so we will be in contact shortly after the closing date to let you know the outcome of your application.#LI-Post

Expected salary

Location

Swindon

Job date

Wed, 09 Oct 2024 07:15:43 GMT

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