Associate Salary in United Kingdom during 2024
π° The median Associate Salary in United Kingdom during 2024 is USD 58,974
βοΈ This salary info is based on 30 individual salaries reported during 2024
Salary details
The average Associate salary lies between USD 50,308 and USD 135,500 in the United Kingdom. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.
- Job title
- Associate
- Experience
- all levels
- Region
- United Kingdom
- Salary year
- 2024
- Sample size
- 30
- Top 10%
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- Top 25%
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- Median
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- Bottom 25%
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- Bottom 10%
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Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.
Last updated:Top 20 Job Tags for Associate roles
The three most common job tag items assiciated with Associate job listings are Python, Engineering and SQL. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:
Python | 3348 jobs Engineering | 2738 jobs SQL | 2499 jobs Machine Learning | 2179 jobs Computer Science | 2039 jobs Statistics | 2021 jobs Research | 1915 jobs R | 1426 jobs Mathematics | 1389 jobs Data management | 1283 jobs Data Analytics | 1276 jobs Testing | 1266 jobs Finance | 1229 jobs Data analysis | 1213 jobs Agile | 1192 jobs AWS | 1137 jobs Excel | 1133 jobs Tableau | 1108 jobs Security | 1050 jobs Architecture | 986 jobsTop 20 Job Perks/Benefits for Associate roles
The three most common job benefits and perks assiciated with Associate job listings are Career development, Health care and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:
Career development | 3616 jobs Health care | 1614 jobs Flex hours | 1361 jobs Competitive pay | 1073 jobs Team events | 995 jobs Startup environment | 855 jobs Wellness | 816 jobs Flex vacation | 669 jobs Equity / stock options | 658 jobs Insurance | 603 jobs Salary bonus | 550 jobs Parental leave | 536 jobs Medical leave | 436 jobs Conferences | 288 jobs Relocation support | 273 jobs Transparency | 243 jobs 401(k) matching | 223 jobs Fitness / gym | 156 jobs Home office stipend | 121 jobs Gear | 88 jobsSalary Composition
In the United Kingdom, the salary for an Associate in AI/ML/Data Science typically consists of a base salary, performance bonuses, and sometimes additional remuneration such as stock options or benefits. The base salary is the fixed component and usually makes up the majority of the total compensation package. Performance bonuses can vary significantly depending on the companyβs policy and your individual performance, often ranging from 5% to 20% of the base salary. Additional remuneration might include stock options, especially in tech startups or larger tech companies, and benefits such as health insurance, pension contributions, and professional development allowances. The composition can vary by region, with London-based roles often offering higher salaries to account for the cost of living. Industry also plays a role; for instance, finance and tech sectors might offer more competitive packages compared to academia or public sector roles. Company size can influence the package as well, with larger companies potentially offering more comprehensive benefits.
Increasing Salary
To increase your salary from an Associate position, consider the following steps:
- Skill Enhancement: Continuously update and expand your technical skills, particularly in high-demand areas like deep learning, natural language processing, or big data analytics.
- Advanced Education: Pursuing a master's degree or Ph.D. in a relevant field can open up higher-level positions and increase earning potential.
- Certifications: Obtain relevant certifications that can validate your skills and make you more competitive.
- Networking: Build a strong professional network to learn about new opportunities and gain insights into industry trends.
- Performance Excellence: Consistently exceed performance expectations to position yourself for promotions and salary increases.
- Industry Transition: Consider moving to industries that offer higher compensation for AI/ML roles, such as finance or tech.
Educational Requirements
Most Associate roles in AI/ML/Data Science require at least a bachelor's degree in a related field such as computer science, mathematics, statistics, or engineering. However, a master's degree is often preferred and can significantly enhance your prospects. Courses in machine learning, data mining, statistical analysis, and programming are particularly beneficial. Some roles may also require knowledge of specific tools and technologies, such as Python, R, SQL, and machine learning frameworks like TensorFlow or PyTorch.
Helpful Certifications
While not always mandatory, certain certifications can be advantageous in demonstrating your expertise and commitment to the field. Some popular certifications include:
- Certified Data Scientist (CDS)
- Microsoft Certified: Azure AI Engineer Associate
- Google Professional Machine Learning Engineer
- AWS Certified Machine Learning β Specialty
- IBM Data Science Professional Certificate
These certifications can help you stand out in a competitive job market and may lead to better job opportunities and salary prospects.
Required Experience
Typically, an Associate role in AI/ML/Data Science requires 1-3 years of relevant experience. This experience can be gained through internships, co-op programs, or entry-level positions in data analysis, software development, or related fields. Practical experience with data manipulation, statistical analysis, and machine learning model development is crucial. Employers often look for candidates who have experience working with large datasets and who can demonstrate problem-solving skills and the ability to apply theoretical knowledge to real-world scenarios.
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