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For Companies At a Glance
- Tasks: Join a dynamic team to analyze data and enhance business decisions using advanced analytics.
- Company: Be part of a leading analytics firm in London or Bromley, driving innovation in the finance sector.
- Benefits: Enjoy a competitive salary up to £60,000 plus bonuses and great benefits.
- Why this job: Work with cutting-edge tools and techniques while making impactful contributions to investment strategies.
- Qualifications: Experience with large data sets, R, Python, or SAS, and a strong background in quantitative analysis required.
- Other info: Collaborate with 50 analysts and contribute to internal labs pushing the boundaries of predictive analytics.
The predicted salary is between 43200 - 84000 £ per year.
Statistical Modelling Analysts
London or Bromley
to £60,000 + bonus & benefits
An opportunity to be part of a cutting-edge analytics team, using data and analytics to guide business decisions to achieve success. Joining a sector market-leader you’ll work in a team of 50 analysts in delivering advanced analytics solutions.
The Role
- Successfully contribute and deliver to the advanced environment of analysts to accurately value portfolios for investment and increase profit on previous purchases.
- Use machine learning and advanced analytical techniques (KNN, XGBoost, etc.) to increase prediction accuracy.
- Continuously improve existing models and create new tools/models for analysis and valuate potential accounts/portfolios. Test and validate results.
- Present and explain valuations and predictions to Investment Committee and Stakeholders.
- Dig into data and raw information through statistical analysis to discover trends and patterns that can be used to extract valuable business insights.
- Develop predictive models, e.g. Scorecards, using statistical tools and techniques.
- Contribute to internal Analytical Labs to keep pushing the boundaries in modelling, predictive analytics and business insights whilst taking advantage of the latest developments in Data Science and analytics.
Candidate Profile
- Significant experience working with large data sets and using quantitative analysis/modelling to drive business results.
- Experience in using statistical computing languages R, Python or SAS to manipulate data and draw insights from those data sets.
- Experience with databases (SQL) would be beneficial.
- Strong problem-solving and creative skills and the ability to exercise sound judgment and make decisions based on accurate and timely analyses.
- Experience and interest in model development.
- High level of integrity and dependability with results-orientation and a strong sense of urgency. Thorough understanding of quantitative analysis preferably from banking and finance industry.
- Ability to communicate and interact with various people at all levels and to present your findings, i.e. be able to explain complex problems in an easy way to non-analysts.
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Statistical Modelling Analysts employer: Aspire Data Recruitment
Contact Detail:
Aspire Data Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Statistical Modelling Analysts
✨Tip Number 1
Familiarize yourself with the specific statistical techniques mentioned in the job description, like KNN and XGBoost. Being able to discuss these methods confidently during your interview will show that you have the technical knowledge they are looking for.
✨Tip Number 2
Prepare examples from your past experience where you've successfully used R, Python, or SAS to manipulate large data sets. Highlighting your hands-on experience with these tools will demonstrate your capability to contribute effectively to the team.
✨Tip Number 3
Practice explaining complex analytical concepts in simple terms. Since the role requires communicating findings to non-analysts, being able to convey your insights clearly will set you apart from other candidates.
✨Tip Number 4
Stay updated on the latest trends in data science and analytics. Showing that you are proactive about learning and applying new techniques can impress the hiring team and align with their goal of pushing boundaries in modelling.
We think you need these skills to ace Statistical Modelling Analysts
Some tips for your application 🫡
Understand the Role: Make sure you fully understand the responsibilities and requirements of a Statistical Modelling Analyst. Highlight your experience with data analysis, machine learning techniques, and statistical computing languages in your application.
Tailor Your CV: Customize your CV to reflect your relevant experience with large data sets, quantitative analysis, and model development. Emphasize your proficiency in R, Python, or SAS, and any experience with SQL databases.
Craft a Compelling Cover Letter: Write a cover letter that showcases your problem-solving skills and your ability to communicate complex analyses clearly. Mention specific examples of how you've used analytics to drive business results in previous roles.
Prepare for Interviews: Be ready to discuss your analytical approach and past projects in detail. Prepare to explain your findings and methodologies in a way that is accessible to non-analysts, as this will be crucial in your role.
How to prepare for a job interview at Aspire Data Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with statistical computing languages like R, Python, or SAS. Highlight specific projects where you used these tools to manipulate data and derive insights, as this will demonstrate your technical proficiency.
✨Demonstrate Problem-Solving Abilities
Prepare examples of how you've tackled complex problems using quantitative analysis. Discuss the methodologies you employed and the impact your solutions had on business outcomes, showcasing your strong problem-solving skills.
✨Communicate Clearly
Practice explaining complex analytical concepts in simple terms. Since you'll need to present findings to non-analysts, being able to communicate effectively is crucial. Use analogies or straightforward language to make your points clear.
✨Stay Updated on Industry Trends
Familiarize yourself with the latest developments in data science and analytics. Being knowledgeable about current trends will not only impress your interviewers but also show your commitment to continuous improvement in the field.
