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- Tasks: Build and optimise machine learning models using Python for impactful decision-support software.
- Company: Join a forward-thinking tech company focused on data-driven solutions.
- Benefits: Remote work, competitive pay, and opportunities for professional growth.
- Why this job: Make a real difference by developing cutting-edge data solutions in a collaborative environment.
- Qualifications: Strong Python skills and experience in machine learning or optimisation techniques required.
- Other info: Dynamic team culture with a focus on innovation and career advancement.
The predicted salary is between 48000 - 72000 £ 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
Data Science Data Science Senior Data Scientist (Python) (Remote) in City of London employer: Pyramid Consulting, Inc
Contact Detail:
Pyramid Consulting, Inc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Data Science Senior Data Scientist (Python) (Remote) in City of London
✨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 job opening or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving Python and machine learning. 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 interview questions. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don't forget to apply through our website! We’ve got some fantastic 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 Data Science Data Science Senior Data Scientist (Python) (Remote) in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, machine learning, and optimisation techniques. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include any relevant projects you've worked on, especially those involving data pipelines or production-ready ML solutions. This gives us a glimpse of your hands-on experience and problem-solving abilities.
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. Explain why you're interested in the role and how you can contribute to our team. We appreciate straightforward communication!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can't wait to hear from you!
How to prepare for a job interview at Pyramid Consulting, Inc
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and the libraries mentioned in the job description, like scikit-learn and pandas. Brush up on your machine learning techniques and be ready to discuss how you've applied them in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific projects where you’ve developed data pipelines or optimisation models. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your impact.
✨Understand the Business Context
Since this role involves engaging with business stakeholders, be ready to explain complex technical concepts in simple terms. Research the company’s products and think about how your work can drive business value.
✨Be Agile and Collaborative
Familiarise yourself with Agile methodologies and be prepared to discuss your experience working in squads. Highlight any contributions to code reviews or technical documentation, as teamwork is key in this role.
