At a Glance
- Tasks: Apply advanced data science techniques to solve real-world commercial problems.
- Company: Leading UK digital organisation driving data and AI transformation.
- Benefits: Hybrid working, competitive day rate, and a collaborative environment.
- Other info: Join a dynamic team focused on innovation and continuous improvement.
- Why this job: Make a tangible impact using cutting-edge data science in a fast-paced setting.
- Qualifications: Experience in data science, Python, and machine learning in commercial environments.
The predicted salary is between 50000 - 70000 € 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
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
- Proven experience in applied Data Science / Machine Learning roles within a commercial environment
- Strong proficiency in Python and SQL
- Hands-on experience with Databricks in a production or enterprise setting
- Experience with ML pipelines, version control (Git), and CI/CD workflows
- Exposure to MLflow or similar model tracking/deployment tools
- Strong foundation in statistics, probability, linear algebra, and applied mathematics
- Experience delivering models such as: Churn prediction models, Customer segmentation frameworks, Next Best Action / propensity models, Time series forecasting models
- MSc, PhD, or equivalent experience in a highly quantitative discipline (e.g. Mathematics, Statistics, Physics, Computer Science, Data Science)
- Strong problem-solving mindset with the ability to manage multiple priorities
- Comfortable working in fast-moving, agile environments
- Able to communicate insights clearly to both technical and non-technical stakeholders
- Collaborative, proactive, and delivery-focused
- Outside IR35 Contract opportunity (duration to be confirmed)
- Hybrid working with regular office presence in Central Manchester
- Day rate to be discussed dependent on candidate experience
- Strong focus on data-driven decision-making and AI-led transformation
- Inclusive, collaborative working environment with modern tooling and practices
Data Scientist employer: Chroma Recruitment
Join a leading digital organisation in Central Manchester that champions innovation and data-driven decision-making. As a Senior Data Scientist, you'll thrive in a collaborative and inclusive environment, leveraging modern cloud-based tools like Databricks to deliver impactful analytics solutions. With a strong emphasis on employee growth and a hybrid working model, this role offers the perfect blend of professional development and work-life balance.
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, attend meetups, and engage in online forums. 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 projects, especially those involving customer churn prediction or recommendation systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the business impact of your work. Be ready to discuss how you've applied machine learning techniques in real-world scenarios, as this is key for roles like the one we're supporting.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find opportunities that match your skills and interests. Plus, it shows you're serious about joining our team and helps us get to know you better.
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 involving Python and Databricks. If you've built and deployed models in a production environment, let us know! This will help us understand your hands-on experience.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language to explain complex concepts, as we value communication skills just as much as technical expertise. Make it easy for us to see your impact!
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 shows you're keen to join our team at StudySmarter!
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 understand the theory but also how to apply it practically.
✨Brush Up on Your Python Skills
Since Python is a key requirement for this role, ensure you're comfortable with its libraries and frameworks relevant to data science. Practise coding challenges or small projects that showcase your ability to build and deploy models, as you might be asked to demonstrate your skills during the interview.
✨Familiarise Yourself with Databricks
Given the emphasis on Databricks in the job description, take some time to explore its features. Understand how to use notebooks, pipelines, and ML workflows effectively. Being able to discuss your experience with Databricks will set you apart from other candidates.
✨Prepare for Cross-Functional Collaboration Questions
This role involves working closely with various teams, so be prepared to discuss your experience collaborating with both technical and non-technical stakeholders. Think of examples where you translated complex data insights into actionable business strategies, as this will highlight your communication skills.
