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For Companies At a Glance
- Tasks: Use your data science skills to solve real-world problems and visualise outcomes.
- Company: Join a forward-thinking company that values innovation and collaboration.
- Benefits: Enjoy competitive pay, health perks, remote work options, and growth opportunities.
- Why this job: Make an impact with cutting-edge technology in a dynamic team environment.
- Qualifications: Master’s degree or 2+ years of relevant experience in data science or ML required.
- Other info: Collaborative culture with excellent career advancement potential.
The predicted salary is between 36000 - 60000 £ per year.
Responsibilities
- 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) is 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).
Key interfaces
- Lead Product Data Scientist
- Other Data Scientists
- Business stakeholders and users
- Software engineers (front-end, back-end, DevOps, data engineers)
- Product & change managers
- BA Digital teams (e.g., architects, application support managers)
- External partners and third parties, as required
- ODS Leadership (Head of Data & Analytics, Head of iOps & Optimisation, Director of ODS)
Key performance indicators
- Model accuracy, performance, and runtime (precision, recall, accuracy)
- Time to develop and deploy features and models
- Data ingestion & processing efficiency and robustness
- Code quality and robustness (e.g., unit test coverage)
- Collaboration and cross-functional teamwork
Data Scientist in London employer: Qualient Technology Solutions UK Limited
Contact Detail:
Qualient Technology Solutions UK Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts 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 projects, especially those involving machine learning and optimisation techniques. Use platforms like GitHub to share your code and visualisations – it’s a great way to demonstrate your expertise.
✨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 both technical and non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your relevant experience and skills, and let us know how you can contribute to our team.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your strong knowledge of machine learning and optimisation techniques in your application. We want to see how you’ve applied these skills in real-life scenarios, so don’t hold back on the details!
Python is Key: Since being fluent in Python is a must, ensure your application reflects your programming prowess. Include specific examples of projects where you've used Python and relevant libraries like scikit-learn or pandas to solve problems.
Tailor Your Application: Take the time to tailor your application to our job description. Mention your experience with cloud platforms, code versioning, and any tools like AWS or Docker that you’ve worked with. This shows us you’re a great fit for the role!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Qualient Technology Solutions UK Limited
✨Know Your Tech Inside Out
Make sure you’re well-versed in the key technologies mentioned in the job description, especially Python and its libraries like scikit-learn and pandas. Brush up on your machine learning techniques and be ready to discuss how you've applied them in real-life scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific problems you've solved using data science and optimisation techniques. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your analytical skills and decision-making process.
✨Familiarise Yourself with Cloud Platforms
Since experience with AWS and cloud-based ML tools is preferred, make sure you understand the basics of these platforms. Be ready to discuss any projects where you’ve used cloud services, and how they helped improve your workflow or model performance.
✨Communicate Clearly and Confidently
You’ll need to explain complex technical concepts to non-technical stakeholders, so practice simplifying your explanations. Think about how you can convey your ideas clearly, and don’t hesitate to ask questions if something isn’t clear during the interview.
