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- Tasks: Build impactful models that influence live fleet operations using applied machine learning.
- Company: Join a forward-thinking company in the heart of London with a hybrid work model.
- Benefits: Enjoy a competitive rate and the flexibility of hybrid working.
- Why this job: Make a real-world impact while working with complex, high-volume data.
- Qualifications: Experience in data science, particularly with time-series and geospatial data.
- Other info: Take ownership of projects from modelling to deployment in a dynamic environment.
The predicted salary is between 36000 - 60000 £ per year.
Location: Hybrid (London, UK)
Contract Duration: Initial 6-12 months
Rate: Competitive
Why this role?
- Real-World Impact: Build models that directly influence live fleet operations
- Applied ML Focus: Time-series, geospatial data, optimisation problems
- Complex Systems: High-volume, real-time operational data
- Autonomy: End-to-end ownership from modelling to deployment
About the Role
We are recruiting on click apply for full job details
Data Scientist - Inside IR35 - Hybrid in Croydon employer: Halian Technology Limited
Contact Detail:
Halian Technology Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Inside IR35 - Hybrid in Croydon
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and projects. This is your chance to demonstrate your applied ML focus and real-world impact, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding complex systems. Be ready to discuss how you've tackled optimisation problems and worked with high-volume, real-time data.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from motivated candidates like you. Plus, it gives us a chance to see your enthusiasm right from the start.
We think you need these skills to ace Data Scientist - Inside IR35 - Hybrid in Croydon
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data science, especially in areas like time-series and geospatial data. We want to see how your skills can directly impact real-world operations!
Showcase Your Projects: Include specific examples of projects where you've built models or worked with high-volume, real-time data. This will help us understand your hands-on experience and applied ML focus.
Be Clear and Concise: When writing your cover letter, keep it straightforward. We appreciate clarity, so get to the point about why you’re a great fit for this role and how you can take ownership from modelling to deployment.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for this exciting opportunity.
How to prepare for a job interview at Halian Technology Limited
✨Know Your Data
Make sure you brush up on your knowledge of time-series and geospatial data. Be ready to discuss how you've applied machine learning techniques to solve optimisation problems in the past. This will show that you understand the complexities of high-volume, real-time operational data.
✨Showcase Your Projects
Prepare to talk about specific projects where you've taken end-to-end ownership, from modelling to deployment. Highlight any challenges you faced and how you overcame them. This demonstrates your autonomy and problem-solving skills, which are crucial for this role.
✨Ask Insightful Questions
Come prepared with questions that show your interest in the company's operations and how your role as a Data Scientist can make a real-world impact. This could include inquiries about their current models or how they handle data integration in live fleet operations.
✨Practice Your Communication Skills
Since you'll be dealing with complex systems, it's essential to communicate your ideas clearly. Practice explaining your past work in simple terms, as you may need to present your findings to non-technical stakeholders. This will help you stand out as a candidate who can bridge the gap between data science and business needs.