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MSc Data Science (Scientific)

Become an agile data scientist ready to work across fields or specialise in one.

Year of entry: 2025 (September)

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Data science skills are now in huge demand across every field of science from particle physics to ecology, from drug design to climate change.

This course will equip you with the skills needed to solve data science questions in different fields of science, and to be agile enough to adapt to new fields and challenges as economic and scientific demands change.

You'll concentrate on the skills which data scientists apply on a daily basis to perform data analyses and to rigorously evaluate the results of those analyses, rather than focusing on theoretical bases or algorithmic structure. This approach will equip you with the skills to succeed even if you don't come from such a formal mathematical or computational background.

This course is led by the Department of Chemistry.

We're 7th in the UK

for Chemistry according to the Complete University Guide 2024

World leading research

The majority of our research was rated 4*, the highest rating in the 2021 Research Excellent Framework

Course content

Over the year, you will study four core modules and two option modules. You will be able to choose option modules that explore a range of different scientific fields, allowing you to tailor the degree to your own academic interests.

You will learn a range of practical skills that are used by data scientists every day, and you will be able to use these skills across a range of different disciplines in future careers. We will also teach you how to read literature from different fields of science, so that you can be prepared to apply that knowledge to new problems.

Modules

Core modules

Option modules

You will study two option modules. Examples can be found below. Some option module combinations may not be possible. The options available to you will be confirmed after you begin your course.

Our modules may change to reflect the latest academic thinking and expertise of our staff, and in line with Department/School academic planning.

Dissertation

Previous research projects within the department include:

  • Reassessing data to find missing chemical modifications
  • Hierarchical cluster analysis of biogenic secondary organic aerosol in Beijing
  • Bioinformatics of Covid-19
  • Identifying stress response regulators in wheat using gene regulatory network modelling
  • Predicting persistent depressive symptoms in older adults

The York approach

Every course at York is built on a distinctive set of learning outcomes. These will give you a clear understanding of what you will be able to accomplish at the end of the course and help you explain what you can offer employers. Our academics identify the knowledge, skills, and experiences you'll need upon graduation and then design the course to get you there.

Students who complete this course will be able to:

  • Design, implement and document computer programs to manage, manipulate and visualise digital data, working by yourself and as a team.
  • Identify and implement appropriate data science and machine learning methods to analyse complex datasets, and to communicate the results to both technical and non-technical audiences.
  • Develop and evaluate training and testing datasets and methods, and use them to critically evaluate the validity, accuracy and limitations of data analyses.
  • Assimilate the data, language, and techniques of previously unfamiliar scientific disciplines; read and critically evaluate the literature to communicate effectively with scientists in those disciplines.
  • Create project proposals which align to professional and ethical standards of a field and apply consultancy skills to provide data science services to scientists in that field.
  • Design, perform and evaluate the outcomes of an independent research project in a data science application area.

Pursuing my MSc in Data Science at the University of York has been an enriching journey, where I had the opportunity to apply my skills to real-world health data through my first research project. The exceptional guidance from professors, combined with a focus on critical thinking, communication, and organisational skills, has truly elevated my academic and personal growth.

Vatsal, MSc Data Science student.

Fees and funding

Annual tuition fees for 2025/26

Study modeUK (home)International and EU
Full-time (1 year) £13,300£31,900

Students on a Student Visa are not currently permitted to study part-time at York.

Fees for students starting in the 2025/26 academic year.

Fees information

UK (home) or international fees? The level of fee that you will be asked to pay depends on whether you're classed as a UK (home) or international student. Check your fee status.

Find out more information about tuition fees and how to pay them.

Funding information

Discover your funding options to help with tuition fees and living costs.

We'll confirm more funding opportunities for students joining us in 2025/26 throughout the year.

If you've successfully completed an undergraduate degree at York you could be eligible for a 10% Masters fee discount.

Funding opportunities

Chevening Scholarships

We are pleased to work with Chevening Scholars to offer funding for our Masters programmes. Chevening Scholarships provide one year of fully-funded postgraduate study in the UK for international (including EU) students. The scholarships are open to early and mid-career professionals who have the potential to become future leaders.

Living costs

You can use our living costs guide to help plan your budget. It covers additional costs that are not included in your tuition fee such as expenses for accommodation and study materials.

Teaching and assessment

You’ll work with world‐leading academics who’ll challenge you to think independently and excel in all that you do. Our approach to teaching will provide you with the knowledge, opportunities, and support you need to grow and succeed in a global workplace.

Teaching format

The course is taught as a combination of lectures and practical workshops, with most modules featuring more workshops than lectures. The teaching is heavily focused on practical data science skills that you will apply in the real world (including the python programming language), rather than on theory and underlying technologies.

Facilities

We have well-equipped computer classrooms for you to access, each with a wide-range of installed software on Windows and Linux-based operating systems.

Teaching location

Most of your teaching will take place in the Department of Chemistry, which is located adjacent to the Science Park, with occasional sessions elsewhere on Campus West. The majority of departments, colleges and facilities are based nearby.

About our campus

Our beautiful green campus offers a student-friendly setting in which to live and study, within easy reach of the action in the city centre. It's easy to get around campus - everything is within walking or pedalling distance, or you can always use the fast and frequent bus service.

Assessment and feedback

Each module consists of 20 credits, with the final research task totalling 60 credits. You will be assessed through computer programmes, written reports, oral presentations and a poster.                                            

Careers and skills

In 2020, the Emerging Job report from LinkedIn listed data scientist at #3, highlighting the demand for this field.

This course will equip you with the scientific and professional skills that data scientists apply on a daily basis. You will learn to work across disciplines and to communicate with non-specialists, allowing you to move with the demands of the sector. Our course will prepare you for a range of science and science-adjacent data science jobs. Likely career destinations include science based industries such as the chemical and pharmaceutical sectors, policy areas such as environment and health policy, as well as academic research.

You'll learn about different types of data, the ethical and practical issues of handling such data, and how to articulate these skills to employers. All of these skills will ensure you are able to work in diverse environments and different job markets.

Career opportunities

  • Data scientist
  • Research scientist
  • Research software engineer
  • Science policy advisor
  • Data analyst
  • Informatician

Transferable skills

  • Team working
  • Self-management
  • Application of IT and numeracy
  • Problem-solving
  • Communication and literacy
  • Consultancy skills

Entry requirements

Typical offer
Undergraduate degree 2:2 or equivalent in a natural science (e.g. Chemistry, Physics, Biology, Environmental Science, Physical Geography), medical science or engineering
Other international qualifications Equivalent qualifications from your country

English language

If English isn't your first language you may need to provide evidence of your English language ability. We accept the following qualifications:

Minimum requirement
IELTS (Academic and Indicator) 6.5, minimum 6.0 in each component
Cambridge CEFR B2 First: 176, with 169 in each component
Oxford ELLT 7, minimum of 6 in each component
Duolingo 120, minimum 105 in all other components
LanguageCert SELT B2 with 33/50 in each component
LanguageCert Academic 70 with a minimum of 65 in each component
Kaplan Test of English Language 459-494, with 426-458 in all other components
Skills for English B2: Merit overall, with Pass with Merit in each component
PTE Academic 61, minimum 55 in each component
TOEFL 87, minimum of 21 in each component
Trinity ISE III Merit in all requirements

For more information see our postgraduate English language requirements.

If you haven't met our English language requirements

You may be eligible for one of our pre-sessional English language courses. These courses will provide you with the level of English needed to meet the conditions of your offer.

The length of course you need to take depends on your current English language test scores and how much you need to improve to reach our English language requirements.

After you've accepted your offer to study at York, we'll confirm which pre-sessional course you should apply to via You@York.

Applying

You can apply and send all your documentation online. You don’t need to complete your application all at once: you can start it, save it and finish it later.

Apply for this course

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