At a Glance
- Tasks: Join our Forensic Data Analytics team to tackle fraud and financial crime using advanced data techniques.
- Company: EY, a global leader in assurance and advisory services, committed to building a better working world.
- Benefits: Competitive pay, flexible working, career development, and a supportive culture.
- Other info: Dynamic environment with opportunities for mentorship and career progression.
- Why this job: Make a real impact by solving complex problems and helping clients navigate sensitive situations.
- Qualifications: Degree in STEM or equivalent experience; proficiency in SQL, Python, and data visualisation tools.
The predicted salary is between 60000 - 80000 € per year.
At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
About the team: As part of the Forensics & Integrity Services, our Forensic Data Analytics team provides advanced analytics services to support high profile and sensitive client matters such as real time fraud detection / prevention, fraud investigations, financial crime, disputes, and litigations. Our work involves developing data and analytics solutions to regularly ingest and monitor data to detect regulatory and compliance risks such as fraud, bribery and corruption, money laundering, sanctions breaches, know your customer failings (KYC), price fixing, mis-selling of financial products, employee misconduct, trader, and market abuse (surveillance), and much more. This is achieved by combining deep forensic investigation knowledge with advanced data engineering and data science techniques such as investigative data linking, social network analysis, statistics, machine learning and large language models.
Your key responsibilities:
- Work with financial services clients, fraud strategy, fraud analytics, fraud investigators, internal and external auditors, lawyers and regulatory authorities in sensitive situations.
- Communicate with clients to scope projects and gather requirements.
- Highlight and explain the outputs of our analytics to clients in the context of their business.
- Be responsible for end-to-end delivery of projects across the full lifecycle - Data extraction, transformation, loading (ETL), analysis, visualisation, deployment and client delivery.
- Handle a large amount of structured and unstructured data from a variety of data sources.
- Carry out reactive and proactive data analysis of large datasets using a wide range of technologies such as Python, SQL and Power BI.
- Supervise the work of junior team members and be responsible for quality control of work products from the team.
- Develop algorithms and solutions to detect, respond, prevent, continually monitor and investigate areas of fraud, bribery & corruption, misconduct and financial crime.
- Apply analytic techniques to prevent, detect, monitor or investigate potentially improper transactions, events or patterns of behaviour related to misconduct, fraud and non-compliance issues.
- Develop supporting material using a suite of visualisation software to clearly present the benefits of the analysis to clients.
- Align to various strategic teams in the areas of technology, innovation and business development.
To qualify for the role, you must have:
- Strong academic qualifications with a degree in a STEM discipline (Computer Science, Engineering, Statistics, Mathematics, etc.) or equivalent work experience.
- Demonstrable proficiency in SQL, Python, Azure data factory and/or Databricks, and Visualization techniques and awareness across other programming languages such as R, C#, JavaScript.
- Ability to work independently, manage work products and mentor junior team members.
- Strong critical thinking, problem-solving skills, understanding of algorithms and appreciation of working with data.
- Excellent communication skills and ability to explain complex analytical concepts to stakeholders from different backgrounds.
Ideally, you’ll also have:
- Domain knowledge of Financial Crime, Market Abuse, Mis-selling remediations, accounting, fraud, bribery and corruption or sector specific knowledge or experience.
- Organisational ability, people skills and project management potential.
- Previous consulting experience and experience with: Relational databases, e.g. SQL Server, PostgreSQL, Oracle, MySQL; Data visualisation software: Spotfire, Tableau, or Power BI; Azure cloud computing platform; Big data technologies such as Spark, Elasticsearch, Hadoop; Statistical techniques (regression, clustering etc.); Machine learning and pattern recognition; Front-end web development e.g. HTML, JavaScript.
We are looking for tenacious and curious individuals with a desire to ‘get to the bottom’ of things. You will be intellectually rigorous, with extremely strong analytical skills, have a passion for data, be adaptable and show an ability to build strong relationships.
What working at EY offers: We offer a competitive remuneration package where you’ll be rewarded for your individual and team performance. Our comprehensive Total Rewards package includes support for flexible working and career development, and with FlexEY you can select benefits that suit your needs, covering holidays, health and well-being, insurance, savings and a wide range of discounts, offers and promotions. Plus, we offer:
- Support and coaching from some of the most engaging colleagues around.
- Opportunities to develop new skills and progress your career.
- The freedom and flexibility to handle your role in a way that’s right for you.
About EY: As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we are dedicated to making EY the best employer.
If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible. Make your mark.
Assurance - Financial Services - Forensic Data Analyst - Senior - London employer: FP&A
At EY, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters inclusivity and innovation. Our London office provides unparalleled opportunities for professional growth, supported by a comprehensive Total Rewards package that includes flexible working arrangements and tailored benefits. Join us to collaborate with talented colleagues, develop your skills, and contribute to meaningful projects that shape the future of financial services.
StudySmarter Expert Advice🤫
We think this is how you could land Assurance - Financial Services - Forensic Data Analyst - Senior - London
✨Tip Number 1
Network like a pro! Reach out to current or former EY employees on LinkedIn. Ask them about their experiences and any tips they might have for landing a role in the Forensic Data Analytics team. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can confidently discuss SQL, Python, and data visualisation techniques. Practise explaining complex concepts in simple terms, as you'll need to communicate effectively with clients from various backgrounds.
✨Tip Number 3
Showcase your problem-solving skills during interviews. Be ready to share examples of how you've tackled data challenges in the past. This will demonstrate your analytical mindset and ability to handle the kind of work EY does in financial crime and compliance.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining EY and building a better working world with us.
We think you need these skills to ace Assurance - Financial Services - Forensic Data Analyst - Senior - London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the role of a Forensic Data Analyst. Highlight your proficiency in SQL, Python, and any relevant data visualisation tools to catch our eye!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about forensic data analysis and how your unique perspective can contribute to our team at EY. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any relevant projects, whether academic or professional, make sure to include them. We love seeing real-world applications of your skills, especially in fraud detection or data analysis.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s straightforward and ensures your application goes straight to the right people at EY!
How to prepare for a job interview at FP&A
✨Know Your Data Tools
Make sure you brush up on your SQL, Python, and any data visualisation tools like Power BI. Be ready to discuss how you've used these in past projects, as well as any challenges you faced and how you overcame them.
✨Understand Financial Crime Concepts
Familiarise yourself with key concepts related to financial crime, fraud detection, and compliance. Being able to speak knowledgeably about these topics will show that you're not just technically skilled but also understand the context of your work.
✨Prepare for Scenario Questions
Expect scenario-based questions where you'll need to demonstrate your problem-solving skills. Think of examples from your experience where you had to analyse large datasets or develop algorithms to tackle specific issues.
✨Showcase Your Communication Skills
Since you'll be explaining complex analytical concepts to clients, practice articulating your thoughts clearly. Use simple language to explain technical details, and prepare to discuss how you've communicated findings to non-technical stakeholders in the past.
