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For Companies At a Glance
- Tasks: Design and develop predictive models to tackle business challenges using cutting-edge data technologies.
- Company: Join a dynamic team focused on innovative analytics solutions in the finance sector.
- Benefits: Enjoy a competitive salary, bonus opportunities, and a range of corporate perks.
- Why this job: Be part of impactful projects, enhance your skills, and work in a collaborative environment.
- Qualifications: Ideal candidates have a math/statistics degree or relevant experience in analytics and project management.
- Other info: Opportunities for mentorship and involvement in white papers and publications.
The predicted salary is between 42000 - 98000 £ per year.
Credit Risk Analytics Consultant
London or Birmingham, to £70,000 plus bonus and benefits
As part of a team, you’ll be involved in designing, developing, and deploying state-of-the-art, data-driven predictive models to solve business problems using the latest technologies in data mining, statistical modeling, pattern recognition, and performance inference.
The Role
- Design and develop state-of-the-art, data-driven exploratory analysis as well as predictive and decision models to solve business problems.
- Build and evaluate predictive and decision models to be deployed in production systems, or for research. This includes the analysis of large amounts of historical data, determining suitability for modelling, data clean-up, pattern identification and variable creation, selection of sampling criteria and performance definition, and variable selection.
- Experiment with different types of algorithms and models, analysing performance to identify the best algorithms to employ.
- Assist with technical product support for new or existing products/services; this includes, but is not limited to, production of sales collateral or ad-hoc investigations initiated by internal or external clients. Work simultaneously on multiple projects of moderate size and complexity.
- Plan effectively to set priorities and manage projects, identify roadblocks and work to get them removed, and understand the importance of meeting deadlines.
- Handle communication with internal and external clients as needed.
- Determine appropriate model report format for communication with clients.
- Participate in authoring white papers, proposals and publications.
- Mentor other scientists and assign modelling tasks when appropriate.
Background
- A graduate, ideally with a mathematical or statistical degree (or a degree with a high level of quantitative, statistical or operational research content) or relevant experience.
- Experience with an analytic solutions or consulting company, and preferably in a client-facing project management capacity.
- Knowledge and experience in applying data to solve business problems through quantitative analysis, experience with predictive modelling and optimisation, and knowledge of the principles and practices of project management.
- Experience with credit risk model developments. Experience with fraud and marketing analytics a plus.
- Strong statistical, data processing and analytical skills.
- An excellent communicator with the ability to explain complex concepts and describe technical material to non-technical users.
- Knowledge of scoring technology and methodologies; model development techniques and tools; advanced statistical methods and quantitative analysis; statistical tools and programs; fluency in SAS, WPL, R, Python or other similar programming language.
Please send your CV or call us on 01706 825 199.
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Credit Risk Analytics Consultant employer: Aspire Data Recruitment
Contact Detail:
Aspire Data Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Analytics Consultant
✨Tip Number 1
Familiarize yourself with the latest technologies in data mining and statistical modeling. Being well-versed in tools like SAS, R, or Python will not only boost your confidence but also demonstrate your technical proficiency during discussions.
✨Tip Number 2
Showcase your experience with predictive modeling and optimization in your conversations. Be prepared to discuss specific projects where you successfully applied these techniques to solve business problems.
✨Tip Number 3
Highlight your project management skills by discussing how you've effectively prioritized tasks and managed multiple projects simultaneously. This will show that you can handle the complexity of the role.
✨Tip Number 4
Prepare to explain complex concepts in simple terms. As an excellent communicator, being able to convey technical information to non-technical users is crucial, so practice articulating your ideas clearly.
We think you need these skills to ace Credit Risk Analytics Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in credit risk analytics, predictive modeling, and statistical analysis. Use specific examples that demonstrate your skills in data-driven decision-making and project management.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data analytics and your understanding of the role. Mention your experience with programming languages like SAS, R, or Python, and how you can contribute to solving business problems.
Highlight Technical Skills: Clearly list your technical skills related to statistical methods, data processing, and model development. Emphasize your experience with algorithms and your ability to communicate complex concepts to non-technical stakeholders.
Prepare for Interviews: Be ready to discuss your previous projects and how you've applied quantitative analysis to solve business challenges. Prepare to explain your thought process when selecting algorithms and models, and be ready to provide examples of your mentoring experience.
How to prepare for a job interview at Aspire Data Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with programming languages like SAS, R, or Python. Highlight specific projects where you applied statistical methods and predictive modeling to solve business problems.
✨Demonstrate Problem-Solving Abilities
Prepare examples of how you've tackled complex data challenges in the past. Discuss your approach to data clean-up, variable selection, and model evaluation, emphasizing your analytical thinking.
✨Communicate Clearly
Practice explaining technical concepts in simple terms. Since you'll be working with non-technical clients, it's crucial to demonstrate your ability to communicate complex ideas effectively.
✨Project Management Skills
Be ready to discuss your experience managing multiple projects. Share how you prioritize tasks, identify roadblocks, and ensure deadlines are met, showcasing your organizational skills.
