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- Tasks: Develop optimisation and machine learning models for decision-support software.
- Company: Leading tech firm at Heathrow with a focus on innovation.
- Benefits: Competitive daily rate, flexible working, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact in the tech industry.
- Qualifications: Master’s degree or 2+ years of relevant experience in data science or ML.
- Other info: Collaborative environment with exciting projects and career advancement potential.
The predicted salary is between 36000 - 60000 £ per year.
Location: Heathrow, Waterside, UK
Job Type: Contract – Inside IR35
Rate: 450 GBP Per Day – Inside IR35
Role purpose: This role is responsible for developing industrialized optimisation and machine learning models as part of a full-stack product squad that delivers operations decision-support software.
Skills/capabilities
- Strong knowledge of either machine learning and optimization techniques, including supervised (regression, tree methods, etc.), unsupervised (clustering) learning, and operations research (linear, mixed integer programming, heuristics).
- Fluent in Python (required) and other programming languages (preferred) with strong skills in applying data science, machine learning, and operations research packages (scikit-learn, pandas, numpy, gurobi, etc.) to solve real-life problems and visualise the outcomes (e.g. seaborn).
- Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g. MLflow).
- Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) - nice to have.
- Experience in code testing (unit, integration, end-to-end tests).
- Strong data engineering skills in SQL and Python.
- Proficient in use of Microsoft Office, including advanced Excel and PowerPoint.
Skills
- Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights.
- Understanding of the trade-offs of different data science, machine learning, and optimization approaches, and ability to intelligently select which are the best candidates to solve a particular business problem.
- Able to structure business and technical problems, identify trade-offs, and propose solutions.
- Communication of advanced technical concepts to audiences with varying levels of technical skills.
- Managing priorities and timelines to deliver features in a timely manner that meet business requirements.
- Collaborative team-working, giving and receiving feedback, and always seeking to improve team processes.
Qualifications/experience
- Master’s degree or greater in data science, machine learning, or operational research, or 2+ years of highly relevant industry experience (required).
- 0-2 years working on production machine learning or optimization software products at scale (required).
- Experience in developing industrialized software, especially data science or machine learning software products (preferred).
- Experience in relevant business domains (transportation, airlines, operations, network problems) (preferred).
Data Scientist in Slough employer: Avensys Consulting UK
Contact Detail:
Avensys Consulting UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Slough
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects. We recommend using GitHub to share your code and visualisations. It’s a great way to demonstrate your expertise in Python and machine learning techniques.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with cloud platforms and optimisation techniques. We suggest practising common data science interview questions to boost your confidence.
✨Tip Number 4
Apply through our website! We make it easy for you to find roles that match your skills. Plus, it shows you’re genuinely interested in joining our team. Don’t miss out on the chance to land that Data Scientist role!
We think you need these skills to ace Data Scientist in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with machine learning, optimisation techniques, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Showcase Your Skills: In your application, don't just list your skills—show us how you've used them! Mention specific tools like Python, scikit-learn, or AWS that you've worked with. We love seeing real-life examples of how you've tackled problems.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language to explain your experience and achievements. We appreciate a well-structured application that gets straight to the good stuff!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we’ll be able to review your application more efficiently. Don’t miss out on this opportunity!
How to prepare for a job interview at Avensys Consulting UK
✨Know Your Tech Inside Out
Make sure you’re well-versed in the machine learning and optimisation techniques mentioned in the job description. Brush up on your Python skills and be ready to discuss how you've applied libraries like scikit-learn and pandas in real-life scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific problems you've solved using data science and machine learning. Think of examples where you had to choose between different approaches and explain why you made those choices. This will demonstrate your analytical skills and understanding of trade-offs.
✨Familiarise Yourself with Cloud Tools
Since experience with cloud platforms like AWS is preferred, make sure you can discuss any relevant projects you've worked on. If you’ve used tools like SageMaker or Docker, be ready to share your experiences and how they contributed to your projects.
✨Communicate Clearly and Collaboratively
Practice explaining complex technical concepts in simple terms. You might be asked to communicate your ideas to non-technical stakeholders, so being able to break down your work will show that you can collaborate effectively within a team.
