Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build predictive models that impact live fleet operations using real-world data.
- Company: Innovative mobility tech company focused on intelligent fleet orchestration.
- Benefits: Competitive rate, hybrid work, and a chance to make a real difference.
- Why this job: Join a high-calibre team solving complex logistics challenges with real-world impact.
- Qualifications: 3+ years in Applied ML or Data Science, strong Python and SQL skills.
- Other info: Exciting opportunity for growth in a dynamic, collaborative 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 behalf of a mobility technology business building intelligent fleet orchestration systems. This role suits an experienced Applied Machine Learning Engineer or Data Scientist comfortable working with messy real-world data, operational constraints, and production systems. You will join a small, high-calibre team solving complex logistics and optimisation challenges with meaningful real-world impact.
Key Responsibilities
- Develop predictive models using time-series and geospatial datasets
- Design and iterate on demand forecasting models
- Support fleet positioning and operational planning initiatives
- Engineer features from large-scale operational datasets using Python and SQL
- Design and evaluate experiments tied to business KPIs
- Collaborate with engineering teams to deploy and improve models in production
- Participate in technical discussions, code reviews, and agile delivery
Required Skills & Experience
Essential: 3-6 years commercial experience in Applied ML or Data Science
- Strong Python (pandas, numpy, sklearn or similar)
- Strong SQL
- Experience building and iterating on predictive models
Conditional (must meet at least 2 of the below):
- Time-series modelling 2 years
- Geospatial data experience (H3, GeoPandas, PostGIS or similar)
- Optimisation / operations research exposure
- Logistics / mobility / marketplace domain experience
Nice to Have:
- Reinforcement learning
- Simulation modelling
- Experience deploying models into cloud environments
- Experimentation frameworks (A/B testing, model validation at scale)
How to Apply
If you’re an Applied ML Contractor looking for a new exciting opportunity working focused on real operational decision systems, get in touch. Please apply if interested and we’ll aim to respond within 24 hours.
Locations
Data Scientist - Inside IR35 - Hybrid in Croydon, Surrey 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, Surrey
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work in mobility tech. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your predictive models and projects related to time-series and geospatial data. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on Python and SQL. Practice coding challenges that focus on data manipulation and model building. We want you to feel confident when discussing your experience with operational data!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we aim to respond within 24 hours, so you won’t be left hanging for long!
We think you need these skills to ace Data Scientist - Inside IR35 - Hybrid in Croydon, Surrey
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with applied machine learning and data science. We want to see how your skills in Python, SQL, and predictive modelling align with the role, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your background fits into our mission of building intelligent fleet orchestration systems. Keep it engaging and personal!
Showcase Real-World Impact: We love seeing how your work has made a difference in previous roles. If you've built models that influenced operations or solved complex problems, make sure to include those examples. It’s all about demonstrating your real-world impact!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we aim to respond within 24 hours, so you won’t be left waiting long!
How to prepare for a job interview at Halian Technology Limited
✨Know Your Data Inside Out
Before the interview, dive deep into the types of data you'll be working with, especially time-series and geospatial datasets. Be ready to discuss how you've handled messy real-world data in the past and share specific examples of predictive models you've built.
✨Showcase Your Technical Skills
Brush up on your Python and SQL skills, as these are crucial for the role. Prepare to demonstrate your proficiency with libraries like pandas and sklearn. You might even want to bring a small project or code snippet to discuss during the interview.
✨Understand the Business Impact
This role is all about real-world impact, so be prepared to talk about how your work can influence fleet operations. Think about previous projects where your models made a difference and be ready to explain the business KPIs you focused on.
✨Engage in Technical Discussions
Since collaboration is key, practice discussing technical concepts clearly and concisely. Be open to feedback and show your willingness to participate in code reviews and agile delivery processes. This will demonstrate your team spirit and adaptability.