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- Tasks: Join a team of ML experts to build impactful models and solutions.
- Company: Be part of one of the UK's largest media companies driving innovation.
- Benefits: Enjoy a competitive salary, bonuses, pension contributions, and flexible working options.
- Why this job: Make a real impact on business problems while collaborating with talented professionals.
- Qualifications: 4+ years in Statistics/ML, strong Python skills, and experience with Big Data.
- Other info: Hybrid working with occasional office visits in London or Berkshire.
The predicted salary is between 54000 - 90000 £ per year.
Are you a pro at building and deploying ML models? Are you tired of just tinkering with the latest tech without actually making a real impact on business problems? Maybe you’d like to join our team of 50 like-minded ML scientists and engineers who work with zero red tape to create practical solutions that actually work.
We’re looking for a Senior Data Scientist who has experience in developing Machine Learning models, evaluating and choosing the tools and technologies, and driving projects. Who are we? We’re one of the UK’s largest media companies, and we’re looking for a Senior Data Scientist to join our Data Science team. Our team works on modeling business problems, including our next generation of intelligent pricing, marketing, and customer engagement tools, building predictive and personalization models, and deploying products at scale.
What should my background look like? You’ll come from a strong statistical analysis/mathematical background with experience in applying solutions to real-world problems. You’ll be able to identify opportunities in data, review code for junior colleagues, and have worked with Data Engineering, Machine Learning, and non-technical stakeholders. You should be comfortable assessing and optimizing processes.
What skills should I have? As our Senior Data Scientist, you will have:
- At least 4 years of experience in Statistics and Machine Learning
- Experience with Python Machine Learning libraries (NumPy, Pandas, SKLearn, etc.)
- At least 3 years of Python programming experience
- Experience applying models to Big Data
- Familiarity with the principles of Continuous Integration and Deployment (CI/CD)
- Familiarity with cloud platforms (we use GCP, but any cloud is fine)
- Ability to translate technical concepts to non-technical colleagues
What’s on offer? There’s a generous base salary of up to £90k, alongside a package including up to 15% bonus, up to 10% matched pension contribution, extensive healthcare and wellness programs, and flexible working. This position offers flexible/hybrid working, but you will be required to attend our offices in London or Berkshire on occasion.
If you feel this is the role for you or want to learn more, click the ‘apply now’ button or contact me using the details provided.
Senior Data Scientist employer: TN United Kingdom
Contact Detail:
TN United Kingdom Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network with current employees or alumni from your university who work in data science. They can provide insights into the company culture and the specific challenges the team faces, which can help you tailor your approach during interviews.
✨Tip Number 2
Stay updated on the latest trends in machine learning and data science. Being able to discuss recent advancements or tools during your conversations with the hiring team will demonstrate your passion and commitment to the field.
✨Tip Number 3
Prepare to showcase your problem-solving skills by discussing past projects where you applied machine learning models to real-world business problems. Be ready to explain your thought process and the impact of your work.
✨Tip Number 4
Familiarise yourself with the company's products and services. Understanding how data science contributes to their business model will allow you to speak more knowledgeably about how you can add value to their team.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in developing Machine Learning models and your statistical analysis background. Use specific examples that demonstrate your ability to solve real-world problems and your familiarity with Python libraries.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how you can contribute to the company's goals. Mention your experience with Big Data and CI/CD principles, and explain how you can bridge the gap between technical and non-technical stakeholders.
Showcase Relevant Projects: If possible, include links to projects or case studies that showcase your work with Machine Learning and data analysis. This could be GitHub repositories or published papers that demonstrate your expertise and impact.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Senior Data Scientist role.
How to prepare for a job interview at TN United Kingdom
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and relevant ML libraries like NumPy, Pandas, and SKLearn. Bring examples of projects where you've successfully applied these tools to solve real-world problems.
✨Demonstrate Your Problem-Solving Ability
Think of specific business problems you've tackled in the past. Be ready to explain your approach to identifying opportunities in data and how you developed solutions that had a measurable impact.
✨Communicate Effectively with Non-Technical Stakeholders
Since you'll be working with non-technical colleagues, practice explaining complex concepts in simple terms. Prepare examples of how you've successfully communicated technical information to diverse audiences.
✨Familiarise Yourself with CI/CD Principles
Understand the basics of Continuous Integration and Deployment, as well as how they apply to machine learning projects. Be ready to discuss any experience you have with deploying models at scale and optimising processes.
