Analytics Associate: Property Data & AVM Insights

Analytics Associate: Property Data & AVM Insights

Full-Time 35000 - 45000 £ / year (est.) No working from home possible
Hometrack

At a Glance

  • Tasks: Analyse property and mortgage data to support insightful decision-making.
  • Company: Join Hometrack, a leading analytics firm in the property sector.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Collaborative team environment with a focus on innovation and development.
  • Why this job: Make an impact by transforming data into valuable insights for clients.
  • Qualifications: Experience with Excel, SQL, and Python; strong analytical skills required.

The predicted salary is between 35000 - 45000 £ per year.

Hometrack is seeking an Analytics Associate to join our London head office within the Analytics and Consulting team.

The role focuses on detailed analyses and modeling of property and mortgage data, providing data analytics support to colleagues and clients.

You will work closely with the team to deliver insightful, data-driven decisions that influence valuation and risk models.

The successful candidate will apply Excel, SQL, and Python to real-world datasets, build BI visuals, present findings

Analytics Associate: Property Data & AVM Insights employer: Hometrack

Hometrack is an exceptional employer that champions innovation and collaboration in the financial services sector. With a strong focus on employee well-being, we offer flexible working arrangements, generous leave policies, and comprehensive benefits, including enhanced paternity leave and financial support for fertility treatments. Our vibrant work culture fosters professional growth through continuous learning opportunities, making it an ideal environment for Senior Machine Learning Engineers to thrive and contribute to meaningful projects.

Hometrack

Contact Details:

Hometrack Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Analytics Associate: Property Data & AVM Insights

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Apply Directly through Our Website

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We think you need these skills to ace Analytics Associate: Property Data & AVM Insights

Communication Skills
Problem-Solving Skills
Attention to Detail
SQL
Python
Automation
Data Engineering

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!

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Craft a Tailored Cover Letter:For a full-time role at Hometrack, 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 Hometrack. 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 Hometrack

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

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Get Comfortable with Python and R

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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.