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- Tasks: Lead model design and calibration for Name List and Transaction Screening systems.
- Company: Join Deutsche Bank, a leading global bank with a commitment to diversity and inclusion.
- Benefits: Enjoy hybrid working, competitive salary, 30 days holiday, and flexible perks.
- Why this job: Be part of a collaborative team focused on career growth and impactful projects.
- Qualifications: Advanced degree in a quantitative field and experience in financial services or FinCrime.
- Other info: Opportunity to support CSR initiatives and volunteer leave.
The predicted salary is between 54000 - 84000 £ per year.
Description
:
Job Title Name List Screening and Transaction Screening Model Strats
Location London
Corporate Title Vice President
Group Strategic Analytics (GSA) is part of Group Chief Operation Office (COO) which acts as the bridge between the Bank’s businesses and infrastructure functions to help deliver the efficiency, control, and transformation goals of the Bank.
You will work within the GSA Team and be responsible for overseeing a global model strategy and deployment of Name List Screening (NLS) and Transaction Screening (TS).
You will work in a collaborative global team and focus on people development and career growth.
You will manage model tuning and development efforts, support regulatory deliverables, and collaborate with cross-functional teams including Compliance, Data Engineering, and Technology.
What we’ll offer you
A healthy, engaged and well-supported workforce are better equipped to do their best work and, more importantly, enjoy their lives inside and outside the workplace. That’s why we are committed to providing an environment with your development and wellbeing at its centre.
You can expect:
Your key responsibilities
Your skills and experience
How we’ll support you
About us
is the leading German bank with strong European roots and a global network. Click to see what we do.
Deutsche Bank in the UK is proud to have been named for six consecutive years. Additionally, we have been awarded a Gold Award from Stonewall and named in their for our work supporting LGBTQ+ inclusion.
If you have a disability, health condition, or require any adjustments during the application process, we encourage you to contact our Adjustments Concierge on to discuss how we can best support you. Alternatively, you can share your phone number, and a member of the team will be happy to call you to talk through your specific requirements.
We strive for a in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.
Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.
We welcome applications from all people and promote a positive, fair and inclusive work environment.
Name List Screening and Transaction Screening Model Strats employer: Deutsche Bank
Contact Detail:
Deutsche Bank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Name List Screening and Transaction Screening Model Strats
✨Tip Number 1
Familiarise yourself with the latest trends in Name List Screening and Transaction Screening. Understanding the current challenges and innovations in these areas will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the financial services sector, especially those involved in compliance and model development. Attend industry events or webinars to build connections that could lead to referrals or insights about the role.
✨Tip Number 3
Brush up on your technical skills, particularly in SQL and Python. Being able to demonstrate your proficiency in these languages during discussions can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your experience with machine learning and artificial intelligence in the context of financial crime. Be ready to share specific examples of how you've applied these technologies in previous roles.
We think you need these skills to ace Name List Screening and Transaction Screening Model Strats
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in model development, risk analytics, and quantitative compliance. Emphasise any specific projects related to Name List Screening or Transaction Screening.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your advanced degree and hands-on experience with SQL and Python make you a perfect fit for the position.
Showcase Relevant Skills: Clearly outline your expertise in machine learning and artificial intelligence, especially in the context of financial crime. Provide examples of how you've applied these skills in previous roles.
Prepare for Technical Questions: Be ready to discuss your experience with data exploration, feature engineering, and statistical analysis. Prepare to explain your approach to model tuning and performance monitoring.
How to prepare for a job interview at Deutsche Bank
✨Understand the Role
Make sure you have a solid grasp of what the Name List Screening and Transaction Screening Model Strats role entails. Familiarise yourself with the key responsibilities, such as model design, calibration, and performance monitoring. This will help you articulate how your skills align with the job.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and any machine learning techniques you've used in model development. Highlight specific projects where you've applied these skills, especially in a financial services or compliance context.
✨Demonstrate Collaborative Spirit
Since the role involves working with cross-functional teams, be ready to share examples of how you've successfully collaborated with others in previous roles. Emphasise your ability to work in agile environments and support team dynamics.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities and analytical thinking. Prepare to discuss how you would approach model tuning or handle anomalies in production environments, using real-life examples to illustrate your thought process.
