At a Glance
- Tasks: Design and deploy impactful machine learning models that drive real commercial decisions.
- Company: Dynamic SaaS organisation focused on next-gen decision-making platforms.
- Benefits: Competitive salary, bonus, hybrid work, and opportunities for professional growth.
- Other info: Join a collaborative team with a product-led culture and clear career progression.
- Why this job: Shape the future of data science with real-world impact and innovative projects.
- Qualifications: Strong experience in machine learning and proven model deployment skills.
The predicted salary is between 85000 - 85000 € per year.
This is a high-impact role within a growing SaaS organisation building a next-generation decisioning platform used by enterprise customers across multiple markets. You’ll be joining at a pivotal moment – moving from project-based analytics to a product-led intelligence capability, where data science directly shapes commercial outcomes, not just dashboards. The core focus is a recommendation and optimisation engine – a product that enables users to make high-value, high-frequency decisions with confidence. Getting the models right – and proving they work – is critical. If you’ve ever been frustrated building models that never make it into production, this is the opposite environment.
What You’ll Be Doing
- Designing and deploying production-grade machine learning models that directly influence commercial decisions
- Building recommendation and optimisation systems across pricing, segmentation, and behavioural modelling
- Developing measurement frameworks to prove real-world impact (not just theoretical accuracy)
- Creating explainable outputs that non-technical users trust and act on
- Working closely with Product, Engineering, and Data to ensure models land and drive outcomes
- Acting as a senior voice within the team – raising standards, reviewing work, and shaping best practice
What We’re Looking For
- Strong experience in machine learning / statistical modelling in production environments
- Proven track record of building models that are deployed, monitored, and used
- Experience working in commercial / product-led environments (not just research or analysis)
- Ability to operate with autonomy – breaking down problems and delivering at pace
- Strong communication – able to translate complex outputs into clear business impact
Nice to have:
- Experience with pricing, optimisation, or recommendation systems
- Familiarity with explainable AI techniques (e.g. SHAP, feature importance)
- Exposure to MLOps / model lifecycle tooling (Databricks, MLflow, etc.)
The Environment
- Modern data stack and tooling (lakehouse architecture, ML pipelines, AI-assisted development)
- Product-led culture – models are expected to ship and deliver impact
- Close collaboration between Data, Product, and Engineering
- Backed by strong investment and a clear roadmap
Why Join
- Work on genuinely complex, high-value problems
- Build models that are actually used day-to-day
- Join a team at an inflection point – where you can shape direction, not just contribute
- Clear progression as the function scales
Senior Data Scientist in Manchester employer: djr
Join a dynamic SaaS organisation in Manchester, where as a Senior Data Scientist, you'll have the opportunity to work on high-impact projects that directly influence commercial outcomes. With a product-led culture and a focus on real-world impact, you will collaborate closely with cross-functional teams, ensuring your models are not just theoretical but actively used in decision-making. Enjoy a supportive work environment that fosters professional growth, offers competitive compensation, and values your contributions in shaping the future of data-driven solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. 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 machine learning models and projects. This is your chance to demonstrate how your work has made a real impact, not just theoretical accuracy.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Be ready to explain complex concepts in simple terms, as you'll need to show that you can translate your technical expertise into business value.
✨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 Senior Data Scientist in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Data Scientist role. Highlight your experience in machine learning and any production-grade models you've built, as this is what we’re really looking for!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re passionate about data science and how you can contribute to our product-led culture. Share specific examples of how your work has influenced commercial decisions in the past.
Showcase Your Communication Skills:Since strong communication is key, make sure to demonstrate your ability to translate complex data outputs into clear business impacts. We want to see how you can make your findings accessible to non-technical users.
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 don’t miss out on any important updates during the process!
How to prepare for a job interview at djr
✨Know Your Models Inside Out
Make sure you can discuss your previous machine learning models in detail. Be ready to explain how they were built, deployed, and the impact they had on business decisions. This shows you not only understand the technical side but also how it translates into real-world outcomes.
✨Showcase Your Communication Skills
Since this role requires translating complex data outputs into clear business impacts, practice explaining your work to someone without a technical background. Use simple language and relatable examples to demonstrate your ability to communicate effectively with non-technical stakeholders.
✨Familiarise Yourself with Their Environment
Research the modern data stack and tools mentioned in the job description, like lakehouse architecture and MLOps. If you have experience with similar technologies, be prepared to discuss how you've used them in past projects and how they can benefit the company.
✨Prepare Questions About Their Product-Led Culture
Think of insightful questions that show your interest in their product-led approach. Ask about how they measure the success of their models or how collaboration between Data, Product, and Engineering works. This demonstrates your enthusiasm for being part of a team that drives impactful decisions.
