Lead Data Scientist - Model Risk Management
Lead Data Scientist - Model Risk Management

Lead Data Scientist - Model Risk Management

London Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead data science projects, focusing on model risk management and AI applications.
  • Company: Join Experian, a global leader in data and technology, transforming industries worldwide.
  • Benefits: Enjoy hybrid working, competitive pay, 25 days leave, and wellness perks.
  • Why this job: Be part of an innovative team making a real impact in financial services.
  • Qualifications: Experience in Python or SAS, model risk management, and analytical tool development required.
  • Other info: Experian values diversity and offers a supportive, inclusive workplace culture.

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.
Qualifications
  • 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.
Additional Information

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: Back on Track! Solutions

Experian is an exceptional employer, offering a dynamic work culture that prioritises diversity, equity, and inclusion while fostering employee growth through innovative projects in data science and analytics. With a hybrid working model, competitive compensation, and a comprehensive benefits package, including generous annual leave and wellness initiatives, employees are empowered to thrive both personally and professionally. Located in London, a hub for technology and finance, Experian provides unique opportunities to engage with leading clients and contribute to impactful solutions in the global market.
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Contact Detail:

Back on Track! Solutions 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. This knowledge will not only help you during interviews but also demonstrate your commitment to staying updated in a rapidly evolving field.

✨Tip Number 2

Network with professionals in the data science and model risk management sectors. Attend relevant meetups or webinars, and connect with current employees at Experian on LinkedIn to gain insights about the company culture and expectations.

✨Tip Number 3

Prepare to discuss specific projects where you've successfully implemented machine learning solutions or managed complex analytical technology projects. Be ready to share how these experiences can translate into value for Experian.

✨Tip Number 4

Understand the regulatory environment surrounding model risk management. Being able to speak knowledgeably about compliance requirements will set you apart as a candidate who is not only technically skilled but also aware of industry standards.

We think you need these skills to ace Lead Data Scientist - Model Risk Management

Expertise in Python and SAS
Model Risk Management knowledge
Experience with Machine Learning algorithms
Analytic consulting skills
Understanding of regulatory requirements for model documentation
Ability to develop and assess analytic tools
Strong project management skills
Excellent communication and presentation skills
Experience in integrating data from various sources
Knowledge of cloud-native big data platforms
Familiarity with Gen AI technologies
Ability to collaborate with cross-functional teams
Problem-solving skills
Adaptability to changing technologies and regulations

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with Python or SAS. Emphasise any previous roles where you managed complex analytical projects or worked in model risk management.

Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about the Lead Data Scientist role at Experian. Mention specific projects or experiences that align with their focus on analytics and AI, and how you can contribute to their goals.

Showcase Your Technical Skills: Clearly outline your technical skills related to machine learning, data analysis, and model documentation. Provide examples of how you've used these skills in past roles, especially in a regulatory environment.

Highlight Collaboration Experience: Since the role involves working with various teams, include examples of successful collaborations in your application. Discuss how you’ve partnered with engineers, product managers, or clients to deliver impactful solutions.

How to prepare for a job interview at Back on Track! Solutions

✨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, and consider bringing examples of your work to the interview.

✨Understand Model Risk Management

Familiarise yourself with the regulatory environment surrounding model risk management. Be ready to discuss how you've navigated compliance requirements in past roles, as this will be crucial for the position.

✨Prepare for Collaborative Scenarios

This role involves working closely with various teams, including Engineering and Analytic Consultants. Think of examples where you've successfully collaborated on complex projects and be ready to share these experiences.

✨Demonstrate Client Engagement Experience

Since the role includes leading client engagements, prepare to discuss your experience in client-facing situations. Highlight any pre-sales activities, training sessions, or demos you've conducted that showcase your ability to maximise client value.

Lead Data Scientist - Model Risk Management
Back on Track! Solutions
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