At a Glance
- Tasks: Lead data science projects, collaborate on AI applications, and engage with clients to maximise value.
- Company: Join Experian, a global leader in data and technology, transforming industries and empowering individuals.
- Benefits: Enjoy hybrid working, competitive pay, 25 days leave, and a focus on wellness and development.
- Why this job: Be part of an innovative team making a real impact in finance and technology.
- Qualifications: Experience in Python or SAS, model risk management, and analytical tool development required.
- Other info: Experian values diversity and offers a supportive culture with numerous awards for workplace excellence.
The predicted salary is between 43200 - 72000 £ per year.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realise their financial goals and help them save time and money.
We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland.
Our Experian Software Solution's Analytics Services Team supports analytic and generative AI products for decisioning, analytics, and fraud and identity globally. As a Lead Data Scientist, you will use your coding expertise (Python, SAS), model risk management and Gen AI knowledge and experience, and analytic consulting skills to lead client and internal engagements for Experian's new global product launch and early client success efforts.
Responsibilities- Collaborate with Engineering and Data Science teams in the design and implementation of Machine Learning, Dashboarding, Ad Hoc Analysis and AI applications in a cloud-native big data platform.
- Partner with Leaders, Analytic Consultants, Engineers, Account Executives, Product Managers, and external partners to bring new innovative solutions to market that provide impact to Experian's broad client base.
- Lead client analytic consulting engagements with financial services clients, including pre-sales and demos, training, and client success activities to maximize client value.
- Leverage Gen AI and model development tools to create and maintain new model document templates to help clients meet Model Risk Management regulatory requirements.
- Stay informed about regulatory changes, technological advancements, and model risk management processes and controls to ensure the technology stack meets all compliance requirements.
- Research and integrate new data assets from different sources into Experian's ML and AI platform.
- Develop and assess analytic tools developed internally and externally.
- Gather feedback from internal and external clients to guide new product development, feature prioritisation, and product evolution of tools and capabilities supported by the Ascend Platform.
- Data science background with development expertise in Python (preferred) or SAS.
- Experience developing models and creating model documentation for Model Risk Management teams in credit or fraud risk and decisioning.
- Understand model risk management regulatory environment and governance requirements for model documentation, validation, and monitoring.
- Experience building analytical tools and providing product and analytic requirements in a regulatory environment.
- A track record for managing complex analytical technology projects.
- The ability to present to all levels of management within Experian and clients.
Benefits package includes:
- Hybrid working
- Great compensation package and discretionary bonus plan
- Core benefits include pension, bupa healthcare, sharesave scheme and more
- 25 days annual leave with 8 bank holidays and 3 volunteering days. You can purchase additional annual leave.
Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; Great Place To Work in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) to name a few.
Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Lead Data Scientist - Model Risk Management employer: Experian
Contact Detail:
Experian Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist - Model Risk Management
✨Tip Number 1
Familiarise yourself with the latest trends in model risk management and generative AI. Being able to discuss recent advancements or regulatory changes during your interview will demonstrate your commitment and knowledge in the field.
✨Tip Number 2
Network with professionals in the data science and analytics community, especially those who work in financial services. Engaging in discussions on platforms like LinkedIn can help you gain insights and potentially get referrals for the position.
✨Tip Number 3
Prepare to showcase your coding skills in Python or SAS through practical examples. You might be asked to solve a problem or explain your thought process, so having a few projects or case studies ready can set you apart.
✨Tip Number 4
Understand Experian's products and services thoroughly. Being able to articulate how your skills and experiences align with their offerings will show that you're not just interested in the role, but also in contributing to their mission.
We think you need these skills to ace Lead Data Scientist - Model Risk Management
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and SAS, as well as your background in model risk management. Use specific examples that demonstrate your skills in developing models and creating documentation relevant to the role.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the Lead Data Scientist position at Experian. Discuss how your previous experiences align with their needs, particularly in analytic consulting and client engagement. Mention your understanding of regulatory environments and how you can contribute to their innovative solutions.
Showcase Relevant Projects: If you have worked on projects related to machine learning, AI applications, or model risk management, be sure to include these in your application. Describe your role, the technologies used, and the impact of your work on the project outcomes.
Highlight Soft Skills: Experian values collaboration and communication. Make sure to highlight your ability to work with cross-functional teams and present complex information clearly to various stakeholders. This will show that you can effectively lead client engagements and contribute to team success.
How to prepare for a job interview at Experian
✨Showcase Your Technical Skills
As a Lead Data Scientist, you'll need to demonstrate your coding expertise in Python or SAS. Be prepared to discuss specific projects where you've applied these skills, particularly in model risk management and AI applications.
✨Understand the Regulatory Environment
Familiarise yourself with the model risk management regulatory requirements relevant to the financial services sector. Being able to articulate how you have navigated these regulations in past roles will show your preparedness for the position.
✨Prepare for Collaborative Scenarios
Expect questions about teamwork and collaboration, as this role involves working closely with various stakeholders. Think of examples where you've successfully partnered with engineers, product managers, or clients to deliver impactful solutions.
✨Demonstrate Your Analytical Mindset
Be ready to discuss how you've developed and assessed analytical tools in previous roles. Highlight your ability to gather feedback and use it to guide product development, showcasing your strategic thinking and problem-solving skills.