543 Data Analyst courses in Leicester delivered On Demand

If spreadsheets give you a headache, this course aims to offer aspirin—metaphorically, of course. The Microsoft Excel Mini Bundle brings clarity to cells, formulas, and functions while adding the human touch of communication and the logic of mathematics. Whether you’re new to data handling or trying to stop formatting rage-quits, this bundle helps you organise, calculate, and interpret with greater ease. From raw entry to meaningful analysis, you’ll gain the structured insight needed to keep rows aligned and heads cool. Learning Outcomes: Learn to use Microsoft Excel for tables, formulas and formatting. Understand data entry principles for structured and clean records. Apply mathematical reasoning to spreadsheets and data calculations. Explore data analysis basics using Excel tools and techniques. Improve communication around data sharing and reporting tasks. Recognise how Excel supports reporting, tracking, and scheduling duties. Who is this Course For: Admins needing Excel structure and clean spreadsheet management. Beginners seeking basic Excel, maths, and data entry knowledge. Office workers handling daily tasks involving spreadsheets. Team members preparing visual reports or internal data logs. Freelancers managing schedules, budgets, and lists via Excel. Analysts looking for a refresher in data visualisation tools. Project coordinators involved in record keeping and communication. Learners improving technical communication in business settings. Career Path: Data Entry Clerk – £22,000/year Junior Data Analyst – £26,000/year Excel Support Administrator – £24,000/year Reporting Assistant – £25,500/year Office Administrator (Excel Focus) – £23,500/year Communication and Data Coordinator – £27,000/year

The Sports Management Mini Bundle is built for those who think strategically about sport. With modules in coaching, agency, bodybuilding theory, first aid and data analysis, it’s an all-rounder for learners who enjoy performance metrics as much as they enjoy structured routines. Whether you're plotting performance growth or analysing athlete progress, this bundle keeps things sharp and informed. It offers insights into coaching strategies, physical development, and the data-driven side of managing sports—ideal for learners who prefer spreadsheets with their sports drinks. Learning Outcomes: Understand contract support and player-agent role responsibilities. Study bodybuilding foundations including muscle function and planning. Learn coaching techniques and team leadership structures. Explore data usage in performance and sports management. Identify first aid procedures for common sports-related injuries. Examine how analytical thinking supports athlete development goals. Who is this Course For: Learners interested in managing or supporting sports talent. Data-focused minds wanting sports metrics explained clearly. Individuals exploring structured coaching and fitness theory. Beginners looking into athlete development and progression tracking. Career starters with an interest in performance support roles. Sports fans curious about strategy, strength, and analysis. Professionals seeking insight into sports administration duties. Students who enjoy structure in athletic planning and performance. Career Path: Sports Data Analyst – £36,000/year Sports Agent – £41,000/year Bodybuilding Coach (Theoretical) – £27,500/year Athlete Liaison Assistant – £29,000/year Fitness Programme Planner – £30,500/year Sports Event Assistant – £26,000/year

Level 5 QLS Endorsed Diploma | 150 CPD Points | +Gifts: QLS Certificate + PDF Certificate | 24/7 Learner Support

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

The Python Mini Bundle offers a clean, structured pathway into essential programming languages and web design basics. Whether you're wrestling with loops or wondering what exactly Go Lang does with its semicolons, this bundle provides clarity across popular technologies—without sounding like a lecture from a sleep-deprived engineer. It starts with Python’s logic, adds HTML and CSS for structure and style, sprinkles in data analysis, and rounds it out with Go Lang—because sometimes, even programmers enjoy a change of pace. It's ideal for learners who enjoy seeing code behave (most of the time) and data that tells a story without emotional outbursts. Learning Outcomes: Understand Python syntax, loops, and structured programming logic. Learn Go Lang structures and execution models for simple programmes. Explore HTML basics and webpage layout fundamentals. Study CSS styling for visual structure and site presentation. Apply Python to explore introductory data analysis techniques. Identify core programming patterns across language types. Who is this Course For: Beginners curious about Python and clean programming logic. Students exploring front-end and back-end web structure theory. Individuals interested in combining coding with data storytelling. Learners wanting to explore multiple programming language basics. Aspiring analysts looking at foundational coding for data handling. Developers transitioning to structured web and code learning. Hobbyists keen to write functional, logical, readable code. Coders who appreciate both syntax and simplicity in language. Career Path: Python Developer – £45,000/year Junior Data Analyst – £30,000/year Web Developer (HTML/CSS) – £32,000/year Go Lang Developer – £48,000/year Software Tester – £34,000/year Front-End Developer – £35,500/year

Uncover Excel 2019's potential through our comprehensive Microsoft Excel course. It empowers you to master features, calculations, data analysis, and automation. Whether you're new to spreadsheets or aiming for data expertise, this course is tailored for you. Our Microsoft Excel course simplifies Excel's complexities, making it beginner-friendly. It equips you with skills vital in today's data-driven landscape. Beyond personal growth, this Microsoft Excel course boosts career prospects. Excel proficiency is valuable in a competitive job market, opening doors to diverse opportunities. Our course is a transformative journey into Excel 2019, unlocking potential, enhancing skills, and advancing careers. Whether you're a novice or aspiring data pro, it's your key to Excel's power and your potential. Learning Outcomes of our Microsoft Excel course: Master Microsoft Excel 2019's latest features. Perform complex calculations with ease. Create visually appealing and well-formatted worksheets. Analyze and visualize data effectively using charts and PivotTables. Automate workbook tasks with Excel VBA. Why buy this Advanced Diploma in Microsoft Excel Complete Course 2019 at QLS Level 7? Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Who is this Advanced Diploma in Microsoft Excel Complete Course 2019 at QLS Level 7 for? Individuals new to Microsoft Excel looking to build a strong foundation. Students and job seekers aiming to enhance their employability. Business professionals wanting to improve data management and analysis skills. Entrepreneurs seeking to streamline their business processes. Anyone interested in harnessing the power of Excel for personal or professional growth. Prerequisites This Advanced Diploma in Microsoft Excel Complete Course 2019 at QLS Level 7 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Analyst: £25,000 - £40,000 per year Financial Analyst: £30,000 - £50,000 per year Business Intelligence Analyst: £30,000 - £55,000 per year Operations Manager: £35,000 - £70,000 per year Project Manager: £40,000 - £70,000 per year Excel VBA Developer: £35,000 - £60,000 per year Certification After studying the course materials of the Advanced Diploma in Microsoft Excel Complete Course 2019 at QLS Level 7 you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for £4.99. Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Microsoft Excel 2019 New Features Introduction to Microsoft Excel 2019 New Features 00:07:00 CONCAT 00:02:00 IFS 00:01:00 MAXIFS 00:01:00 MINIFS 00:01:00 SWITCH 00:02:00 TEXTJOIN 00:01:00 Map Chart 00:02:00 Funnel Chart 00:01:00 Better Visuals 00:06:00 Pivot Table Enhancements 00:02:00 Power Pivot Updates 00:01:00 Getting Started with Microsoft Office Excel Navigate the Excel User Interface 00:28:00 Use Excel Commands 00:10:00 Create and Save a Basic Workbook 00:19:00 Enter Cell Data 00:12:00 Use Excel Help 00:05:00 Performing Calculations Create Worksheet Formulas 00:15:00 Insert Functions 00:17:00 Reuse Formulas and Functions 00:17:00 Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Formatting a Worksheet Apply Text Formats 00:16:00 Apply Number Format 00:08:00 Align Cell Contents 00:09:00 Apply Styles and Themes 00:12:00 Apply Basic Conditional Formatting 00:11:00 Create and Use Templates 00:08:00 Printing Workbooks Preview and Print a Workbook 00:10:00 Set Up the Page Layout 00:09:00 Configure Headers and Footers 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working with Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:23:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:12:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Sharing and Protecting Workbooks Collaborate on a Workbook 00:19:00 Protect Worksheets and Workbooks 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Excel VBA Data Management Create a Macro Using the Macro Recorder 01:00:00 Edit a Macro 01:00:00 Debug a Macro 00:30:00 Customize the Quick Access Toolbar and Hotkeys 00:30:00 Set Macro Security 01:00:00 Insert Text 00:30:00 Format Text 00:30:00 Sort Data 00:30:00 Duplicate Data 01:00:00 Generate a Report 01:00:00 Determine the Dialog Box Type 00:15:00 Capture User Input 01:00:00 Insert, Copy, and Delete Worksheets 00:30:00 Rename Worksheets 00:30:00 Modify the Order of Worksheets 00:15:00 Print Worksheets 00:30:00 Create User-Defined Functions 00:30:00 Automate SUM Functions 00:30:00 Excel Templates Excel Templates 00:00:00 Resources Resources - Microsoft Excel - Beginner Course - Cpd Accredited 00:00:00 Mock Exam Mock Exam - Microsoft Excel Complete Course 2019 00:20:00 Final Exam Final Exam - Microsoft Excel Complete Course 2019 00:20:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Think libraries are just about stamping books? Think again. This bundle gets under the hood of modern library and information management—where cataloguing meets GDPR, and dusty shelves make way for digital systems. From document control to basic IT and data analysis, this bundle suits anyone working behind the scenes to keep information flowing neatly (and legally). Ideal for those who believe alphabetising can be an art form and spreadsheets deserve proper formatting. 🟪 Learning Outcomes: Manage library records using structured documentation methods. Apply GDPR principles to safeguard personal and public data. Organise and retrieve digital files using basic IT skills. Analyse usage data to support service development decisions. Maintain orderly systems for both physical and digital resources. Understand key tasks in library and information management. 🟪 Who Is This Course For: Library assistants supporting daily resource and data handling. Archive staff maintaining structured and secure records. Admins in educational or public library environments. Data handlers working in knowledge or resource centres. Entry-level staff in information management roles. Professionals dealing with document control and storage. Staff helping with catalogue management and updates. Anyone allergic to messy filing systems and loose ends. 🟪 Career Path (UK Average Salaries): Library Assistant – £22,000/year Document Controller – £27,000/year Information Support Officer – £26,000/year Records Management Assistant – £25,000/year Digital Archive Coordinator – £28,000/year Data Analyst (Library/Info Sector) – £30,000/year

With clinical coding rising in demand, this Mini Bundle focuses on the necessary groundwork to help you understand data structure, biology terminology, healthcare systems, and pharmacy documentation. It suits learners looking to blend organisational skills with science without peering down a microscope or being on call. Alongside healthcare and coding fundamentals, you’ll touch on time management and the functions of pharmacy technicians—ideal for those with a knack for detail. It’s neat, specific, and logical. And let’s be honest: few things are as satisfying as correctly labelling things (especially in healthcare). Learning Outcomes: Understand healthcare terminology for accurate medical coding. Explore how biology supports clinical coding accuracy. Learn pharmacy roles in relation to patient data. Understand public health systems and health reporting. Apply coding principles with structured healthcare knowledge. Develop time planning skills in coding-based roles. Who Is This Course For: Future clinical coders interested in healthcare systems. Public health students focusing on record interpretation. Admin staff in GP practices and clinics. Pharmacy support staff managing medication records. Healthcare data processors needing structure knowledge. Beginners in health informatics and coding. Professionals transitioning from admin to coding roles. Students exploring scientific admin roles in healthcare. Career Path: Clinical Coding Officer – £30,000/year Healthcare Data Analyst – £32,000/year Pharmacy Technician (Data Role) – £26,000/year Health Records Analyst – £28,500/year Medical Audit Assistant – £27,000/year Medical Information Administrator – £25,500/year

Level 7 QLS Endorsed Diploma | 180 CPD Points | +Gifts: QLS Certificate + PDF Certificate | 24/7 Learner Support

Insurance finance demands accuracy, detailed analysis, and a strong grasp of numbers. This mini bundle covers payroll, accounting, forensic accounting, data analysis, and tax—all key skills for anyone involved in insurance financial functions. This bundle offers a solid foundation in how insurance firms manage their accounts and analyse data to detect discrepancies or trends. Whether your role involves payroll, tax reporting, or investigative accounting, these courses deliver clear, focused knowledge that supports decision-making and operational accuracy. Fully online and structured, it avoids jargon and instead provides a direct, practical approach to financial management within insurance. Learning Outcomes: Understand payroll processes within insurance finance environments. Apply accounting principles relevant to insurance operations. Use forensic accounting techniques to investigate financial records. Analyse data to support insurance financial decisions. Gain knowledge of tax regulations affecting insurance firms. Develop skills to support insurance financial reporting accuracy. Who Is This Course For: Insurance finance staff handling payroll and tax duties. Accountants specialising in insurance industry requirements. Data analysts working with insurance financial datasets. Investigators involved in forensic accounting for insurance claims. Tax professionals managing insurance-related tax filings. Payroll officers within insurance companies. Auditors reviewing insurance financial compliance. Students or professionals entering insurance finance roles. Career Path (UK Average Salaries): Insurance Accountant – £35,000 per year Payroll Officer – £28,000 per year Forensic Accountant – £40,000 per year Data Analyst (Insurance) – £33,000 per year Tax Advisor – £38,000 per year Insurance Auditor – £36,000 per year