At a Glance
- Tasks: Apply advanced data science techniques to solve real-world commercial problems and build scalable models.
- Company: Join a leading UK digital organisation driving data and AI transformation.
- Benefits: Enjoy hybrid working, competitive pay, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and enhance your skills in a dynamic setting.
- Why this job: Make a tangible impact using cutting-edge technology in a fast-paced environment.
- Qualifications: Experience in machine learning, Python, and production data science environments required.
The predicted salary is between 60000 - 80000 € per year.
We are supporting a large UK-based digital organisation undergoing a significant data and AI transformation, with growing demand for advanced analytics across commercial and customer-focused teams. This is a contract opportunity within a fast-moving Data Science function, working in a modern cloud-based environment. The role sits within a commercial analytics team focused on delivering measurable business impact through applied machine learning and production-grade data science.
Key Focus Areas (Must-Have Experience)
- Built and deployed customer churn prediction models in a commercial environment
- Developed Next Best Action / recommendation systems to drive customer engagement and value
- Delivered customer segmentation models (e.g. clustering, behavioural segmentation, lifecycle modelling)
- Strong experience in time series analysis and forecasting (e.g. demand, revenue, customer behaviour trends)
- Worked end-to-end in production data science environments, not just proof-of-concept models
- Strong hands-on experience using Python as a primary programming language
- Experience working within Databricks (notebooks, pipelines, or ML workflows)
- A strong mathematical and statistical background, with confidence in applying theory to real commercial problems
Role Overview
You will apply advanced data science and machine learning techniques to solve complex commercial and customer problems. This includes building scalable models, deploying them into production, and ensuring ongoing performance and governance. You will work closely with cross-functional teams including data engineering, analytics, architecture, and business stakeholders to ensure models are embedded effectively into decision-making processes.
Responsibilities
- Apply statistical, mathematical, and machine learning techniques to solve real-world commercial problems
- Develop, validate, deploy, and monitor machine learning models in production environments
- Build and maintain end-to-end data science solutions using modern MLOps practices
- Use cloud-based platforms (notably Databricks) to develop scalable data products
- Translate complex analytical outputs into clear, business-focused insights
- Collaborate with technical and non-technical stakeholders across multiple functions
- Ensure compliance with governance, regulatory, and internal data standards
- Continuously improve model performance, robustness, and business impact
Data Scientist employer: Chroma Recruitment
Join a forward-thinking digital organisation in Central Manchester that champions innovation and collaboration within its Data Science team. With a hybrid working model, employees enjoy a flexible work-life balance while contributing to impactful projects that drive customer engagement and business growth. The company fosters a culture of continuous learning and development, offering ample opportunities for professional advancement in a dynamic and supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the lookout for opportunities. Attend meetups or webinars related to data science to meet potential employers and learn about job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving customer churn prediction models or recommendation systems. This will give you an edge and demonstrate your hands-on experience in a commercial environment.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python, Databricks, and machine learning techniques. Practise explaining complex concepts in simple terms to impress both technical and non-technical interviewers.
✨Tip Number 4
Don't forget to apply through our website! We have plenty of exciting opportunities that match your skills. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with customer churn prediction models and any relevant machine learning projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include specific examples of your work, especially those that demonstrate your hands-on experience with Python and Databricks. We love seeing real-world applications of your skills, so don’t hold back on the details!
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. Make it personal and engaging – we want to get to know you!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Let’s make this happen together!
How to prepare for a job interview at Chroma Recruitment
✨Know Your Models Inside Out
Make sure you can discuss the customer churn prediction models and recommendation systems you've built in detail. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This shows you not only have the technical skills but also the practical experience needed for the role.
✨Brush Up on Your Python Skills
Since Python is a key requirement, ensure you're comfortable discussing your hands-on experience with it. Prepare to talk about specific libraries you've used, such as Pandas or Scikit-learn, and be ready to solve a coding challenge during the interview. Practising common data manipulation tasks can really help!
✨Understand the Business Impact
Be prepared to translate your technical work into business outcomes. Think of examples where your models led to measurable improvements in customer engagement or revenue. This will demonstrate that you understand the commercial side of data science, which is crucial for this role.
✨Familiarise Yourself with Databricks
Since the role involves working within Databricks, make sure you know how to navigate notebooks, pipelines, and ML workflows. If you have any experience with cloud-based platforms, be ready to share how you've used them to develop scalable data products. This will show you're not just a theorist but someone who can hit the ground running.
