At a Glance
- Tasks: Lead data science projects and develop impactful machine learning models.
- Company: Dynamic digital organisation driving data and AI transformation.
- Benefits: Hybrid working, competitive pay, and opportunities for contract extension.
- Other info: Collaborative culture focused on innovation and professional growth.
- Why this job: Make a real impact in a fast-paced environment with cutting-edge technology.
- Qualifications: Experience in data science, Python, and cloud-based platforms like Databricks.
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)- Led data science projects in a commercial or enterprise environment
- 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 lead the development and delivery of data science products that generate measurable business value. Working closely with cross-functional teams, you will guide technical delivery from concept through to production, ensuring solutions are scalable, robust, and aligned to business and regulatory requirements. You will also support team capability development where required, contribute to a high-performance culture, and help position data science as a strategic internal consultancy function within an outside IR35 engagement.
Responsibilities- Lead the development of data science products from ideation to production deployment
- 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 project capability with a hands-on technical mindset
- Comfortable working in fast-moving, agile environments
- Able to communicate insights clearly to both technical and non-technical stakeholders
- Collaborative, proactive, and delivery-focused
- Hybrid working with regular office presence in Central Manchester
- Strong focus on data-driven decision-making and AI-led transformation
- Inclusive, collaborative working environment with modern tooling and practices
Data Science Lead in Manchester employer: Chroma Recruitment Ltd
Join a leading digital organisation in Central Manchester that champions innovation and data-driven decision-making. With a strong focus on employee growth, you will thrive in a collaborative and inclusive environment, leveraging modern tools and practices to make a tangible impact through advanced analytics. Enjoy the flexibility of hybrid working while contributing to a high-performance culture that values your expertise in data science.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Lead in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving customer churn prediction or recommendation systems. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and being ready to discuss your past projects in detail. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Data Science Lead in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Science Lead role. Highlight your experience with customer churn prediction models and any relevant projects you've led. We want to see how your skills align with our needs!
Showcase Your Projects:In your application, don’t just list your skills—show us what you’ve done! Include specific examples of data science projects you've worked on, especially those that had a measurable business impact. This helps 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 need to see how well you can communicate insights to both technical and non-technical stakeholders.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to track your application and ensure it reaches the right people. Don’t miss out!
How to prepare for a job interview at Chroma Recruitment Ltd
✨Know Your Data Science Projects
Before the interview, brush up on your past data science projects. Be ready to discuss specific examples where you led initiatives, especially those involving customer churn prediction or recommendation systems. This will show your practical experience and how it aligns with the role.
✨Master the Technical Skills
Make sure you're comfortable discussing Python, SQL, and Databricks. Prepare to answer technical questions or even solve problems on the spot. Practising coding challenges related to machine learning and MLOps can give you a solid edge.
✨Communicate Clearly
You’ll need to translate complex analytical outputs into business insights. Practice explaining your work in simple terms, as you'll likely be speaking with both technical and non-technical stakeholders. Clear communication can set you apart from other candidates.
✨Show Your Collaborative Spirit
This role involves working closely with cross-functional teams. Be prepared to share examples of how you've successfully collaborated in the past. Highlight your proactive approach and how you contribute to a high-performance culture.
