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Data scientist in London

What is the Data Scientist Salary in London 2024?

5 min read

Wondering what the data scientist salary in London is? You’ve come to the right place! London, with its bustling tech scene and vibrant economy, stands as a hub for data science talent. But what truly defines a good salary for a data scientist in London?

This varies depending on a range of factors. From experience and qualifications to the industry and company size, these can all have an impact.

What is a Good Salary for a Data Scientist in London?

A good salary for a data scientist in London is around £40,000 to £70,000 per year. For this salary benchmark, you will typically be qualified and have a few years of experience under your belt. 

What is a High Salary for a Data Scientist in London?

A high salary will vary greatly depending on the company and size of the organisation but you can expect to receive £80,000 to £100,000+ per year. For this type of salary, you will usually be required to lead a team of data scientists through recruitment and training, while overseeing the organisation's data science strategy. 

Additionally, you could be implementing new systems and processes to enhance data flow and identify opportunities for improvement. Other roles could include assessing emerging technologies and representing the company at external events and conferences, building and maintaining client relationships to drive business growth.

Salary sign

What is the Average Salary for a Data Scientist in London?

The average wage in London for a data scientist is £59,551 per year. This takes into consideration the lowest and highest salaries to work out the median. Don’t forget, there are lots of things to take into consideration though as some organisations might offer better salaries but slower career progression routes. So what is better suited to one person might not be for another. It all comes down to your personal circumstances. 

What is a Low Salary for a Data Scientist in London?

Entry-level salaries can be much lower. For instance, if you’re doing a data scientist apprenticeship, the employer can pay you a minimum of £6.40 in your first year. Some employers will often pay you higher than this though!

However, if you’re 19+ years old and in your second year, you will be entitled to the National Minimum Wage for your age range regardless. 

Data scientist graduate schemes and junior data scientists typically begin with salaries ranging from £25,000 to £30,000. Remember, that this is all valuable as you will be gaining essential experience and sometimes even further qualifications and training. 

What Factors can Impact the Data Scientist Salary in London and why?

Let’s delve into the data to uncover the factors that shape salary expectations for data scientist jobs in London: 

Benefits

Some common work benefits for data scientist jobs may include:

  • Pension schemes: This provides you with a retirement savings plan often with the employer matching contributions.

  • Healthcare benefits: These can range from medical, dental, and vision insurance coverage for the employee and sometimes their dependents.

  • Flexible working: Some employers encourage flexible working which can enable employees to have a work-life balance by working at a time that suits their lifestyle. 

  • Remote or hybrid working: When working remotely and hybrid, you can save on travel costs. Some people may prefer this kind of environment, whereas others might prefer to be based in the office for the social aspect of it. This all depends on whatever your personal preference is. 

  • Professional Development: Your employer will require you to stay current in the data scientist field. Therefore, they might contribute to or cover payment in full for training courses, conference attendance, or certifications.

  • Performance bonuses or profit shares: Some organisations will give additional compensation based on individual or team performance, often tied to achieving specific goals or targets.

There are other benefits companies may offer so if this is important to you, make sure to take that into account when applying for data scientist jobs.

Experience

Experience is essential for building a successful career in data science. Given the multidisciplinary nature of the field, which requires technical skills, domain knowledge, and problem-solving abilities, gaining experience allows professionals to improve and deepen their expertise in these areas.

Qualifications

Qualifications also play a significant role in a data scientist's career. While experience provides practical skills and knowledge, qualifications such as degrees, certifications, and specialised training demonstrate a foundational understanding of key concepts and methodologies in data science. 

These qualifications can enhance credibility, open doors to job opportunities, and help professionals stay competitive in the field. Additionally, pursuing continuous education and obtaining relevant qualifications allows data scientists to stay updated with the latest trends and advancements, ensuring they remain effective contributors in an ever-evolving field.

Industry

Different industries have varying data needs, challenges, and opportunities, shaping the types of projects data scientists are involved in and the skills they need to excel. For example, a data scientist working in finance may focus on risk assessment and algorithmic trading, while one in healthcare may analyse patient data for clinical research or personalised medicine. This can influence the salary levels that a data scientist will receive. 

Two data scientists in health care

Company Size

The company size can have a significant impact on the salary of a data scientist. Generally, larger companies tend to offer higher salaries compared to smaller ones. This is because they have more financial resources allocated, and they may have more extensive and complex data sets, requiring sophisticated analysis and insights. 

However, that’s not to say a smaller employer isn’t more suited to your requirements. If you’re looking for greater flexibility, a closer-knit work environment, and the opportunity to have a more significant impact on projects then a smaller organisation might be better suited for you!

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