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- Tasks: Build predictive models and analyse real commercial datasets using machine learning techniques.
- Company: Leading consultancy in the Commercial Sales arena with exciting growth opportunities.
- Benefits: Competitive salary, bonus, remote work, and additional benefits.
- Other info: Flexible remote work with just one day a month in the office.
- Why this job: Join a new machine learning team and make a real impact on innovative projects.
- Qualifications: Experience in data science, Python, and machine learning techniques.
The predicted salary is between 50000 - 50000 £ per year.
Initial 12 mth FTC £50,000+ Bonus + Benefits - Remote working
My client is a leading Consultancy in the Commercial Sales arena helping Businesses and Retailers all across the UK. Due to exciting growth, we are building a new machine learning team. With most of the team in place, we are looking for a Data Scientist (Machine Learning) to support the build and launch of our new Microsoft Fabric Lakehouse and machine learning platform. This is a largely remote role with on average just 1 day a month required in the office.
The Data Scientist (Machine Learning) will apply statistical and machine learning techniques to real commercial datasets, producing outputs such as impact analysis, ROI modelling, forecasting, and anomaly detection. The emphasis is on practical model delivery, documentation, and handover, rather than long-term operational ownership.
As our new Data Scientist (Machine Learning) you will be responsible for:
- Build predictive, forecasting and anomaly-detection models
- Perform feature engineering validation using Python / PySpark
- Work in Fabric Notebooks, Delta Lakehouse, and AutoML
- Embed models into production pipelines with our Data Engineering team
- Document and hand over deliverables
Data Scientist (Machine Learning) employer: 360 Resourcing Solutions
Contact Detail:
360 Resourcing Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Machine Learning)
✨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 machine learning projects. Use platforms like GitHub to share your code and results. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python, PySpark, and any relevant machine learning techniques. Practice common interview questions to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented Data Scientists. Keep an eye on our listings and make sure your application stands out by tailoring it to the role.
We think you need these skills to ace Data Scientist (Machine Learning)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist (Machine Learning) role. Highlight your experience with machine learning techniques, Python, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of your work in machine learning, especially those that involve predictive modelling or anomaly detection. We love seeing real-world applications of your skills, so don’t hold back on sharing your successes!
Keep It Clear and Concise: When writing your application, clarity is key! Use straightforward language and avoid jargon unless it’s necessary. We appreciate a well-structured application that gets straight to the point without fluff.
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 360 Resourcing Solutions
✨Know Your Tech Stack
Make sure you’re familiar with the tools mentioned in the job description, like Python, PySpark, and Microsoft Fabric. Brush up on your knowledge of these technologies and be ready to discuss how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific examples where you've applied machine learning techniques to solve real-world problems. Highlight your experience with predictive modelling, ROI analysis, and anomaly detection to demonstrate your practical skills.
✨Understand the Business Context
Since this role is in a consultancy setting, it’s crucial to understand how data science impacts business decisions. Research the company’s clients and think about how your work could drive value for them. This will show that you’re not just a techie but also a strategic thinker.
✨Prepare for Collaboration Questions
You’ll be working closely with the Data Engineering team, so be ready to discuss your experience in collaborative environments. Think of examples where you’ve successfully documented and handed over deliverables, as well as how you’ve embedded models into production pipelines.