Data Scientist

Data Scientist

Bolton Freelance 36000 - 54000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Develop advanced data-driven solutions using machine learning techniques.
  • Company: Join an industry-leading technology company focused on innovation.
  • Benefits: Earn up to £450 per day with hybrid work options.
  • 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: Contract role for 6 months, rolling basis; feedback may not be provided to all applicants.

The predicted salary is between 36000 - 54000 £ 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

Join an industry-leading technology company that values innovation and collaboration, offering a dynamic work culture where your contributions as a Data Scientist will directly impact business success. With competitive pay of up to £450 per day and the flexibility of a hybrid working model in Manchester, you'll have the opportunity to grow your skills in a supportive environment while tackling complex data challenges alongside a high-performing team.
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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 readiness for the role.

✨Tip Number 2

Make sure you have hands-on experience with Python, as it's a key requirement for this position. Consider working on personal projects or contributing to open-source projects that showcase your Python skills and ability to implement machine learning models.

✨Tip Number 3

Since the role involves bridging data science and data engineering, brush up on your knowledge of ETL pipelines. Be prepared to discuss how you've worked with data pipelines in the past and how you can apply that experience to this role.

✨Tip Number 4

If you have experience with cloud platforms like AWS, Azure, or GCP, be ready to highlight specific projects where you've utilised these technologies. This will show that you're not only familiar with the tools but also know how to leverage them effectively in a data science context.

We think you need these skills to ace Data Scientist

Machine Learning Techniques
Linear Regression
XGBoost
Ensemble Methods
Python Programming
ETL Pipeline Development
AWS
Azure
GCP
SHAP Tool Familiarity
LIME Tool Familiarity
Data Engineering Skills
Statistical Analysis
Data Visualisation
Problem-Solving Skills
Collaboration Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience with machine learning techniques, Python, and any relevant ETL pipelines. Use specific examples to demonstrate your expertise in these areas.

Craft a Strong Cover Letter: In your cover letter, explain why you are interested in the Data Scientist role and how your skills align with the company's objectives. Mention your familiarity with tools like SHAP or LIME, as well as your experience with cloud platforms such as AWS, Azure, or GCP.

Showcase Relevant Projects: If you have worked on projects that involved developing machine learning models or bridging data science and engineering, be sure to include these in your application. Highlight the impact of your work and any quantifiable results.

Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which is crucial for a Data Scientist role.

How to prepare for a job interview at Formula Recruitment

✨Showcase Your Technical Skills

Be prepared to discuss your experience with machine learning techniques like linear regression and XGBoost. Bring examples of projects where you've successfully implemented these models, as this will demonstrate your expertise and problem-solving abilities.

✨Familiarise Yourself with ETL Processes

Since the role involves bridging data science and engineering, be ready to talk about your experience with ETL pipelines. Highlight any specific tools or frameworks you've used, and how they contributed to your data-driven solutions.

✨Discuss Cloud Experience

The job mentions AWS, Azure, or GCP, so make sure you can discuss your experience with these platforms. Be specific about the services you've used and how they helped in deploying machine learning models or managing data.

✨Prepare for Scenario-Based Questions

Expect questions that assess your problem-solving skills in real-world scenarios. Think of examples where you've had to use SHAP or LIME tools to explain model predictions, and be ready to articulate your thought process clearly.

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