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- Tasks: Design and implement analytics solutions for complex business challenges using your quantitative skills.
- Company: Join a leading bank with a focus on innovation and risk management.
- Benefits: Competitive salary, professional development, and a supportive work environment.
- Why this job: Make a real impact by solving critical financial problems with advanced analytics.
- Qualifications: Experience in quantitative modelling and strong Python programming skills required.
- Other info: Dynamic role with opportunities for growth in a collaborative team.
The predicted salary is between 54000 - 84000 £ per year.
Empirical Search • London, UK
Role Description
- Design analytics and modelling solutions to complex business problems using domain expertise.
- Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools.
- Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams.
- Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them.
- Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users.
- Demonstrate conformance to all the Bank’s Enterprise Risk Management Policies, particularly Model Risk Policy.
- Ensure all development activities are undertaken within the defined control environment.
Role Requirements
- Experience in developing quantitative behavioural models in Asset Liability & Management.
- Deep understanding of statistical and econometric modelling techniques – e.g. time series analysis, regression models and various estimation techniques.
- Excellent communication skills, including the ability to discuss technical matters with a non-technical audience as well as being proficient in python programming.
- Previous experience in modelling non-maturing deposits, mortgage prepayment or mortgage completion models.
- Strong experience in analysing large volumes of data including cleaning and subsequent pattern identification and clustering.
- Experience developing, implementing of models which utilise more complex Machine learning techniques.
AVP - Treasury Quantitative Analytics employer: Empirical Search
Contact Detail:
Empirical Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AVP - Treasury Quantitative Analytics
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your analytics and modelling solutions. Use real-world examples that demonstrate your expertise in statistical techniques and programming. This will make you stand out when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex concepts in simple terms, especially if you're talking to non-technical folks. This will help you shine during those crucial conversations.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace AVP - Treasury Quantitative Analytics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AVP - Treasury Quantitative Analytics role. Highlight your experience with quantitative behavioural models and any relevant statistical techniques you've used. We want to see how your skills align with what we're looking for!
Showcase Your Communication Skills: Since you'll need to explain complex concepts to non-technical folks, make sure to include examples of how you've done this in the past. We love seeing candidates who can bridge the gap between technical and non-technical audiences!
Demonstrate Your Technical Proficiency: Don't forget to mention your programming skills, especially in Python! If you've worked on analytics or modelling solutions before, share those experiences. We’re keen to know how you’ve implemented models and ensured their effectiveness.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come through our own channels!
How to prepare for a job interview at Empirical Search
✨Know Your Models Inside Out
Make sure you can discuss your experience with quantitative behavioural models in detail. Be ready to explain the techniques you've used, like time series analysis and regression models, and how they apply to Asset Liability & Management.
✨Brush Up on Your Python Skills
Since proficiency in Python is key for this role, ensure you're comfortable discussing your coding experience. Prepare to showcase any relevant projects or examples where you've implemented analytics and models using Python.
✨Communicate Clearly
You’ll need to explain complex technical concepts to non-technical audiences. Practice simplifying your explanations and think of examples where you've successfully communicated intricate ideas in a straightforward manner.
✨Demonstrate Your Analytical Mindset
Be prepared to discuss your experience with data analysis, especially in cleaning data and identifying patterns. Think of specific instances where you've tackled large datasets and how you approached the challenges involved.