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- Tasks: Join a dynamic team to build cutting-edge machine learning models and optimise operations.
- Company: Innovative tech company focused on data-driven solutions in a collaborative environment.
- Benefits: Competitive pay, flexible working arrangements, and opportunities for professional growth.
- Why this job: Make a real impact by developing high-impact data solutions that drive business success.
- Qualifications: Strong Python skills and experience with machine learning and optimisation techniques required.
- Other info: Exciting opportunity for career advancement in a fast-paced, supportive team.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for a Data Scientist to join a full-stack product squad delivering operations decision-support software. This role focuses on building industrialised optimisation and machine learning models, working end-to-end from problem definition to production deployment.
You will collaborate closely with product, engineering, and business stakeholders to deliver high-impact, data-driven solutions.
Key Responsibilities- Develop data pipelines, machine learning, and optimisation models in Python
- Build and industrialise ML/optimisation algorithms using best-practice software engineering principles
- Implement automated data cleaning pipelines and workflow orchestration (e.g. Dagster)
- Integrate ML/optimisation models into full product stacks (data ingestion, UI, orchestration)
- Deploy solutions using CI/CD in a cloud environment
- Build robust logging, testing (unit/regression), and error-handling frameworks
- Analyse adoption, performance, and business value of deployed models
- Engage with business stakeholders to gather requirements and feedback
- Contribute to Agile squad ways of working, code reviews, and technical documentation
- Strong knowledge of machine learning and/or optimisation techniques (Regression, Tree methods, Clustering, Linear / Mixed-Integer Programming, Heuristics)
- Strong Python experience (scikit-learn, pandas, numpy, optimisation libraries)
- Experience building production-ready ML or optimisation solutions
- Solid understanding of CI/CD, Git version control, and cloud platforms (AWS preferred)
- Strong data engineering skills in Python and SQL
- Experience with automated testing (unit, integration, end-to-end)
- Ability to communicate complex technical concepts to non-technical stakeholders
- Experience with MLflow, DVC, SageMaker
- Workflow orchestration tools (Dagster / Airflow)
- Containerisation (Docker, ECS)
- Domain experience in transportation, airlines, operations, or network optimisation
- Master’s degree in Data Science, ML, Operational Research OR
- 2+ years of highly relevant industry experience
- 0–2 years experience working on production ML/optimisation products at scale
Senior Data Scientist in Slough employer: Pyramid Consulting, Inc
Contact Detail:
Pyramid Consulting, Inc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist in Slough
✨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 hunt for a new gig. You never know who might have the inside scoop on a role that’s perfect for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving machine learning and optimisation. 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 knowledge and practising common data science questions. Be ready to discuss your experience with Python, CI/CD, and cloud platforms like AWS – these are hot topics!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented data scientists like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Senior Data Scientist in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and optimisation techniques. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
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. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Technical Skills: When detailing your experience, focus on your Python skills and any relevant tools you've used, like scikit-learn or AWS. We’re keen to know how you’ve built production-ready solutions in the past!
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’s super easy!
How to prepare for a job interview at Pyramid Consulting, Inc
✨Know Your Tech Inside Out
Make sure you brush up on your machine learning and optimisation techniques. Be ready to discuss specific algorithms you've worked with, like regression or clustering, and how you've implemented them in Python. This will show that you’re not just familiar with the concepts but have practical experience too.
✨Showcase Your Problem-Solving Skills
Prepare to talk about a project where you defined a problem and delivered a data-driven solution. Highlight your end-to-end process, from building data pipelines to deploying models. This will demonstrate your ability to think critically and work collaboratively with stakeholders.
✨Familiarise Yourself with CI/CD Practices
Since this role involves deploying solutions in a cloud environment, be ready to discuss your experience with CI/CD and version control using Git. Mention any specific tools you’ve used, like AWS, and how they helped streamline your workflow.
✨Communicate Clearly with Non-Techies
You’ll need to explain complex technical concepts to non-technical stakeholders, so practice simplifying your language. Think of examples where you successfully communicated your ideas and how it benefited the project. This will show your versatility and ability to engage with different teams.
