Credit Insights Specialist: Forecasting & Data Visualization in London

Credit Insights Specialist: Forecasting & Data Visualization in London

London Full-Time 59400 - 72600 £ / year (est.) No working from home possible
NewDay

At a Glance

  • Tasks: Transform complex data into actionable insights and create visual dashboards.
  • Company: Join NewDay, a forward-thinking company in the credit sector.
  • Benefits: Enjoy competitive pay, flexible working, and opportunities for growth.
  • Other info: Collaborative environment with diverse teams and career advancement potential.
  • Why this job: Make a real impact by driving informed business decisions with data.
  • Qualifications: Strong analytical skills and experience with data visualisation tools.

The predicted salary is between 59400 - 72600 £ per year.

New Day is seeking a Specialist, Credit Insights to turn complex data into actionable insight across the credit lifecycle in the UK.

You will forecast arrears and assess risks, interrogating large datasets and building scalable analytics processes.

You will visualise findings for stakeholders, create dashboards, and collaborate across Credit Risk, Finance, Strategy and Data teams to drive informed business decisions.

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Credit Insights Specialist: Forecasting & Data Visualization in London employer: NewDay

NewDay is an exceptional employer located in the vibrant city of London, offering a dynamic work culture that fosters innovation and collaboration. With a strong emphasis on employee growth, we provide ample opportunities for professional development and skill enhancement, particularly in the field of analytics. Our hybrid work environment ensures flexibility, allowing you to balance your personal and professional life while contributing to meaningful projects that drive profitability and strategic success.

NewDay

Contact Details:

NewDay Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Credit Insights Specialist: Forecasting & Data Visualization in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like NewDay!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Credit Insights Specialist: Forecasting & Data Visualization at NewDay.

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like NewDay.

Apply Directly through Our Website

When you find a suitable opening like Credit Insights Specialist: Forecasting & Data Visualization at NewDay, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Credit Insights Specialist: Forecasting & Data Visualization in London

Data Analysis
Forecasting
Data Visualisation
Dashboard Creation
Stakeholder Collaboration
Credit Risk Assessment
Analytics Process Development

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at NewDay, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at NewDay. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at NewDay

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at NewDay!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.