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- Tasks: Join us as a Data Scientist to analyze data and improve housing services!
- Company: We're a leading provider of affordable homes in the East Midlands, committed to community sustainability.
- Benefits: Enjoy a competitive salary, 34 days off, flexible work, and extensive training opportunities.
- Why this job: Make a real impact in social housing while working with cutting-edge data analytics tools.
- Qualifications: You need SQL expertise, programming skills in Python or R, and a background in data science.
- Other info: This is a hybrid role, perfect for balancing work and life!
The predicted salary is between 35800 - 46500 £ per year.
Job Description
- Competitive salary
- 34 days annual leave (including statutory days), increasing with length of service (pro-rata for part time)
- Contributory pension scheme
- Flexible working
- A wide range of training and development opportunities (we are an Investors in People accredited organisation)
Data Scientist employer: Iris
Contact Detail:
Iris Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarize yourself with the social housing sector. Understanding the specific challenges and opportunities in this field will help you tailor your insights and recommendations effectively.
✨Tip Number 2
Brush up on your SQL skills, as this is crucial for working with large databases. Consider practicing with real datasets to enhance your ability to extract and manipulate data efficiently.
✨Tip Number 3
Get comfortable with data visualization tools. Being able to present complex data in an accessible way is key, so practice creating dashboards and reports that can be easily understood by non-technical stakeholders.
✨Tip Number 4
Showcase your experience with machine learning libraries. Highlight any projects where you've applied TensorFlow, Scikit-learn, or PyTorch, as this will demonstrate your technical expertise and problem-solving skills.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Scientist position. Understand the key responsibilities and required skills, especially in SQL, Python, and data analytics.
Tailor Your CV: Customize your CV to highlight relevant experience in data science, particularly your work with large databases, machine learning frameworks, and statistical modeling. Use specific examples that demonstrate your expertise.
Craft a Compelling Cover Letter: Write a cover letter that reflects your understanding of the social housing sector and how your skills align with the company's values of Integrity, Diversity, and Excellence. Be sure to express your enthusiasm for the role.
Highlight Your Technical Skills: In your application, emphasize your proficiency in programming languages like Python or R, and your experience with machine learning libraries. Mention any industry certifications you hold in data science or related fields.
How to prepare for a job interview at Iris
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, R, and machine learning libraries. Bring examples of past projects where you utilized these skills to solve real-world problems, especially in the context of data analysis and predictive modeling.
✨Understand the Social Housing Sector
Research the social housing sector and be ready to discuss how data science can improve housing services. Demonstrating knowledge about current challenges and opportunities in this field will show your genuine interest and fit for the role.
✨Prepare for Data Presentation
Since the role involves presenting complex data to non-technical stakeholders, practice explaining your findings clearly and concisely. Use visual aids or dashboards from previous work to illustrate your points effectively.
✨Align with Company Values
Familiarize yourself with the company's values of Integrity, Diversity, Openness, Accountability, Clarity, and Excellence. Be ready to share examples of how you embody these values in your work and how they align with your professional philosophy.
