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- Tasks: Use your data science skills to solve real-world problems and visualise outcomes.
- Company: Join a dynamic team at Waterside, UK, focused on innovation.
- Benefits: Competitive contract pay, flexible work arrangements, and opportunities for growth.
- Why this job: Make an impact with cutting-edge machine learning and optimisation techniques.
- Qualifications: Strong Python skills and experience in data science and machine learning.
- Other info: Collaborative environment with a focus on continuous improvement and feedback.
The predicted salary is between 36000 - 60000 £ per year.
We have an exciting job opportunity for a Sr./Lead Data Scientist role at Waterside, UK - Contract.
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) is nice to have.
- Experience in code testing (unit, integration, end-to-end tests).
- Strong data engineering skills in SQL and Python.
- Proficient in the 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.
Data Scientist in London employer: LSA Recruit
Contact Detail:
LSA Recruit 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 folks in the industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Scientist gig.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning and data visualisation. We want to see how you tackle real-life problems, so make sure to highlight your Python prowess and any cool tools you've used.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practising common data science interview questions and coding challenges. Don’t forget to articulate your thought process clearly – communication is key!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So, don’t hesitate – get your application in and let’s get the conversation started!
We think you need these skills to ace Data Scientist in 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, Python, and any relevant cloud platforms. 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 techniques. Whether it's clustering or regression, we love seeing real-life applications of your skills. Don't forget to mention the tools you used!
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. Explain why you're a great fit for the role and how you can contribute to our team at StudySmarter. We appreciate straightforward communication!
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 don’t miss out on any important updates from us!
How to prepare for a job interview at LSA Recruit
✨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 to tackle real-life problems.
✨Showcase Your Cloud Skills
Since experience with cloud platforms like AWS is preferred, be prepared to talk about any projects where you've utilised these tools. If you've worked with ML tools like SageMaker or have experience in CI/CD processes, make sure to highlight that!
✨Communicate Clearly
You’ll need to explain complex technical concepts to people who might not have a tech background. Practice simplifying your explanations and think of examples that illustrate your points without getting too bogged down in jargon.
✨Be a Team Player
Collaboration is key! Be ready to discuss how you’ve worked in teams, given and received feedback, and contributed to improving processes. Share specific examples that demonstrate your ability to manage priorities and deliver results on time.
