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- Tasks: Develop advanced data-driven solutions using machine learning techniques.
- Company: Join an industry-leading technology company at the forefront of innovation.
- Benefits: Earn up to £450 per day with hybrid work options and a rolling contract.
- Why this job: Work on complex projects in a high-performing team that values your expertise.
- Qualifications: Experience with ML techniques, Python, and cloud platforms like AWS or Azure required.
- Other info: This role is outside IR35, offering flexibility and competitive pay.
The predicted salary is between 90000 - 135000 £ per year.
Contract role: Data Scientist : Up to £450 per day Outside IR35: 6 months rolling : Hybrid – Weekly
An industry-leading technology company is looking for an experienced Data Scientist to play a pivotal role in developing advanced data-driven solutions, leveraging machine learning techniques to support business objectives and customer requirements.
As a Data Scientist, you will bring expertise in developing and implementing machine learning models, and bridging the gap between data science and data engineering where necessary.
As a Data Scientist, you will be experienced with:
- ML techniques – linear regression, XGBoost, ensemble methods
- Python
- ETL pipelines
- AWS, Azure, or GCP
- SHAP or LIME tool familiarity
Key information:
- Up to £450 per day Outside IR35
- 6 months (rolling)
- Hybrid Weekly – Manchester
This is an exciting opportunity for a Data Scientist to work on complex solutions and development within a high-performing team.
Contract role: Data Scientist : Up to £450 per day Outside IR35: 6 months rolling : Hybrid – Weekly
*Unfortunately, due to the high volume of applications, not all submissions will receive feedback.
Data Scientist employer: Formula Recruitment
Contact Detail:
Formula Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the specific machine learning techniques mentioned in the job description, such as linear regression and XGBoost. Being able to discuss these methods confidently during an interview will demonstrate your expertise and understanding of the role.
✨Tip Number 2
Make sure you can articulate your experience with Python and any relevant libraries or frameworks. Prepare examples of projects where you've successfully implemented machine learning models, as this will showcase your practical skills.
✨Tip Number 3
Since the role involves bridging data science and data engineering, be ready to discuss your experience with ETL pipelines. Highlight any projects where you've worked on data integration or transformation, as this will show your versatility.
✨Tip Number 4
If you have experience with cloud platforms like AWS, Azure, or GCP, prepare to discuss how you've used these tools in your previous roles. This knowledge is crucial for the position and will set you apart from other candidates.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with machine learning techniques like linear regression and XGBoost. Include specific projects where you've implemented these skills.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for data science and your understanding of the role. Mention your familiarity with ETL pipelines and cloud platforms like AWS or Azure, and how you can contribute to the company's objectives.
Showcase Technical Skills: In your application, emphasise your proficiency in Python and any experience with SHAP or LIME tools. Providing examples of how you've used these in past projects can strengthen your application.
Follow Application Instructions: Ensure you follow all application instructions carefully. If the job posting specifies certain documents or formats, make sure to adhere to those requirements to avoid any issues during the review process.
How to prepare for a job interview at Formula Recruitment
✨Showcase Your Machine Learning Expertise
Be prepared to discuss your experience with various machine learning techniques, such as linear regression and XGBoost. Bring examples of projects where you've successfully implemented these models to solve real-world problems.
✨Demonstrate Your Python Skills
Since Python is a key requirement for this role, ensure you can talk about your proficiency in it. Consider discussing specific libraries you've used, like Pandas or Scikit-learn, and how they contributed to your data analysis and model development.
✨Familiarise Yourself with ETL Processes
Understanding ETL (Extract, Transform, Load) pipelines is crucial. Be ready to explain your experience in building or managing these processes, and how they integrate with data science workflows.
✨Know Your Cloud Platforms
This role mentions AWS, Azure, or GCP, so brush up on your knowledge of these platforms. Be prepared to discuss any projects where you've utilised cloud services for data storage, processing, or machine learning deployment.
