Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead projects using geospatial data to enhance investment decisions in real estate.
- Company: A top global investment management firm committed to diversity and inclusion.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Why this job: Make a real impact on investment strategies while working with advanced analytics.
- Qualifications: Degree in a relevant field and over four years of experience in data science.
- Other info: Collaborative environment with a focus on innovation and value creation.
The predicted salary is between 43200 - 72000 £ per year.
A leading global investment management firm is seeking an experienced Data Scientist to optimize investment decision-making through advanced analytics and geospatial data science. This role entails leading projects that generate value for real estate investments while collaborating with internal and external stakeholders.
Ideal candidates should have a degree in a relevant field and over four years of experience, with proficiency in Python and a strong interest in data science techniques. A commitment to diversity and inclusion is part of our culture.
Geospatial Data Scientist – Real Estate & Private Assets employer: Schroders
Contact Detail:
Schroders Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Geospatial Data Scientist – Real Estate & Private Assets
✨Tip Number 1
Network like a pro! Reach out to professionals in the geospatial data science field on LinkedIn or at industry events. Building connections can lead to job opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and geospatial analytics. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process clearly, as collaboration with stakeholders is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s a great way to ensure your application gets noticed.
We think you need these skills to ace Geospatial Data Scientist – Real Estate & Private Assets
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in geospatial data science and investment management. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data science and how you can contribute to our team. We love seeing candidates who are genuinely excited about the role and our mission.
Showcase Your Technical Skills: Since proficiency in Python is key for this role, make sure to mention any relevant projects or experiences where you've used Python effectively. We’re keen to see your technical prowess in action!
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’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Schroders
✨Know Your Geospatial Data
Make sure you brush up on your geospatial data science knowledge. Be prepared to discuss specific projects where you've used Python for data analysis, especially in real estate contexts. Highlight how your work has optimised decision-making.
✨Showcase Collaboration Skills
Since this role involves working with various stakeholders, think of examples that demonstrate your ability to collaborate effectively. Prepare to share stories about how you’ve successfully led projects and engaged with both internal teams and external partners.
✨Emphasise Diversity and Inclusion
Familiarise yourself with the company's commitment to diversity and inclusion. Be ready to discuss how you can contribute to this culture, whether through your own experiences or by promoting diverse perspectives in your work.
✨Prepare for Technical Questions
Expect technical questions related to data science techniques and Python programming. Brush up on your coding skills and be ready to solve problems on the spot. Practising common data science scenarios can give you an edge.
