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- Tasks: Build machine learning models and deliver insights that drive business value.
- Company: SPG Resourcing connects top talent with data-driven companies across the UK.
- Benefits: Enjoy a full-time role with opportunities for growth and collaboration in a dynamic team.
- Other info: Work from York or Manchester and engage in diverse projects across various business areas.
- Why this job: Join a cross-functional team and make a real impact using cutting-edge AI technologies.
- Qualifications: Proficiency in Python, experience with machine learning, and strong communication skills required.
The predicted salary is between 28800 - 48000 £ per year.
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This range is provided by SPG Resourcing . Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
Direct message the job poster from SPG Resourcing
Data Recruitment Consultant | Connecting Top Talent with Data-Driven Companies | North of the UK
Job Title: Data Scientist
Job Type: Permanent
Location: York or Manchester (UK)
About the Role
This role offers the opportunity to work across diverse business areas, building machine learning and statistical solutions that drive real business value. You\’ll join a cross-functional team of data scientists, engineers, and analysts using agile methods. As a Data Scientist, you will work closely with stakeholders to deliver models and insights related to pricing, decision-making, policy management, and more. You\’ll be expected to both build models and communicate their value clearly to the business.
Key Responsibilities
- Apply the full data science lifecycle: from problem design to model deployment and monitoring.
- Build production-grade machine learning models and manage their lifecycle (monitoring, retraining, etc.).
- Analyse diverse datasets (internal and 3rd party), applying statistical and machine learning methods.
- Collaborate with pricing teams, data engineers, and business units to deliver value.
- Write high-quality Python code following best practices.
- Continuously research and apply new tools, techniques, and technologies.
Experience with:
Cloud deployment,Neural networks and libraries like TensorFlow, XGBoost, CatBoost, SKlearn, API development, SQL,CI/CD, DevOps, or MLOps pipelines
Experience with:
- Strong hands-on experience or genuine interest in data science and analytics.
- Proficiency in Python and familiarity with testing frameworks (e.g., pytest).
- Ability to work both independently and in collaborative teams.
- Understanding of machine learning applications to business problems.
- Strong communication and presentation skills.
- Experience with version control and software development practices.
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Science, Analyst, and Engineering
-
Industries
Information Technology & Services, Financial Services, and Insurance
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Data Scientist employer: SPG Resourcing
Contact Detail:
SPG Resourcing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest machine learning frameworks and libraries mentioned in the job description, such as TensorFlow and XGBoost. Being able to discuss your hands-on experience or projects using these tools can set you apart during interviews.
✨Tip Number 2
Prepare to showcase your ability to communicate complex data insights clearly. Practice explaining your past projects and how they delivered business value, as this is a key responsibility of the role.
✨Tip Number 3
Network with professionals in the data science field, especially those who work in similar roles or companies. Engaging with them on platforms like LinkedIn can provide valuable insights and potentially lead to referrals.
✨Tip Number 4
Stay updated on industry trends and advancements in data science. Being knowledgeable about recent developments can help you demonstrate your passion for the field and your commitment to continuous learning during interviews.
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 and statistical solutions. Include specific projects or achievements that demonstrate your skills in Python, cloud deployment, and collaboration with cross-functional teams.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with the responsibilities of building production-grade models and your ability to communicate insights effectively to stakeholders.
Showcase Technical Skills: Clearly outline your technical skills in your application. Mention your proficiency in Python, experience with libraries like TensorFlow and SKlearn, and familiarity with CI/CD practices. This will help demonstrate your capability to handle the technical demands of the role.
Prepare for Interviews: If you get called for an interview, be ready to discuss your previous projects in detail. Prepare to explain your thought process in problem design, model deployment, and how you've applied machine learning to solve business problems. Strong communication skills are key!
How to prepare for a job interview at SPG Resourcing
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, machine learning libraries like TensorFlow and SKlearn, and any cloud deployment knowledge. Bring examples of projects where you've applied these skills to solve real business problems.
✨Communicate Clearly
As a Data Scientist, you'll need to explain complex models and insights to non-technical stakeholders. Practice articulating your thought process and the value of your work in simple terms to demonstrate your communication skills.
✨Demonstrate Problem-Solving Ability
Expect to face scenario-based questions that assess your problem-solving skills. Prepare to walk through your approach to tackling data-related challenges, from problem design to model deployment and monitoring.
✨Research the Company and Role
Understand the specific business areas the company operates in and how data science contributes to their goals. Tailor your responses to show how your skills align with their needs and express genuine interest in their projects.