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- Tasks: Develop optimisation and machine learning models for decision-support software.
- Company: Join a leading company at Heathrow, shaping the future of operations.
- Benefits: Competitive daily rate, flexible working, and opportunities for professional growth.
- Why this job: Make a real impact with your data skills in a dynamic environment.
- Qualifications: Master’s degree or 2+ years of relevant experience in data science or ML.
- Other info: Collaborative team culture with a focus on innovation and improvement.
The predicted salary is between 72000 - 108000 £ 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 City of London 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 City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. 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 data science projects, especially those using Python and machine learning techniques. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with various audiences.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application.
We think you need these skills to ace Data Scientist 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 machine learning, optimisation techniques, and any relevant programming languages like Python. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've applied data science or machine learning techniques. Whether it's a personal project or something from your previous job, we love seeing real-life applications of your skills. Don't forget to mention the tools you used!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're passionate about data science and how you can contribute to our team. Be sure to mention your understanding of the trade-offs in different approaches and how you can solve business problems.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy to do!
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 used libraries like scikit-learn and pandas in real-life projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data science problems in the past. Be ready to explain your thought process, the trade-offs you considered, and how you arrived at your solutions. This will demonstrate your analytical skills and ability to apply different techniques effectively.
✨Familiarise Yourself with Cloud Tools
Since experience with cloud platforms like AWS is preferred, make sure you understand the basics of tools like SageMaker and how CI/CD processes work. If you’ve worked with Docker or GitHub Actions, have specific examples ready to share.
✨Communicate Clearly and Collaboratively
Practice explaining complex technical concepts in simple terms. The interviewers will want to see how you can communicate with team members who may not have a technical background. Also, be prepared to discuss how you handle feedback and work within a team.
