ESCP Business Analytics Master: Admissions Guide for 2027

What is the ESCP MSc in Business Analytics & AI?

The ESCP MSc in Business Analytics & AI is a 15-month, full-time master's taught entirely in English. It was previously called the MSc in Big Data and Business Analytics, so if you search for ESCP Big Data and Business Analytics, this is the same programme under its current name.

The programme runs in stages:

• July to September: online core management modules with on-site exams, compulsory only if your degree has fewer than 240 ECTS.
• October to March: Paris campus.
• April to June: Berlin or Madrid, plus a one-week international seminar in Beijing.
• July to December: an internship of at least four months anywhere in the world, plus a professional thesis.

Courses include machine learning, R, data mining, NLP and text mining, database management, data visualisation, and marketing and financial analytics, along with Entrepreneurship and Innovation in the AI era. ESCP says about 75% of students are international, from more than 40 nationalities, with backgrounds ranging from engineering to literature.

ESCP Business Analytics master requirements

• A bachelor's degree with at least 180 ECTS, in any discipline.
• An English score (TOEFL, TOEIC listening and reading, or IELTS) from the last two years. No minimum is published.
• Transcripts, CV, passport or ID and a photo; two reference letters are recommended.

The programme page lists no GMAT, GRE or formal maths prerequisite. The curriculum is quantitative, though, so your file should show you can handle statistics and coding.

Application process and ESCP business analytics deadlines

You apply online (€130 for one specialisation, €195 for two). Eligible candidates have a personal interview with the academic director and professionals from the sector. Admitted students confirm with a €3,600 deposit, deducted from tuition.

Tuition and career outcomes

ESCP business analytics fees for the 2027 intake total around €28,200: €17,500 for core courses, €7,800 for the specialisation and €2,900 of additional fees, which include AI tools and software licences. A €3,600 supplement applies if your degree has fewer than 240 ECTS. Fees change each year and exclude travel and housing.

In ESCP's survey of the class of 2024, 83% were working within three months, 91% had jobs with an international dimension and the average salary was €60,000. Consulting (28%) and IT (24%) were the leading sectors, with roles such as data scientist and AI consultant at firms including BCG, Capgemini Invent, Deloitte and KPMG.

Other ESCP routes into data and AI careers

If you want a broader management degree first, read our guide to ESCP MiM admissions. ESCP also offers related MSc programmes in Digital Transformation Management & Leadership and in Product Management for Technology (both London and Paris). From 2027, the new ESCP School of Technology will focus on AI, data and emerging technologies, as explained in our ESCP Business School overview.

How to stand out in your ESCP Business Analytics master application

• Show evidence of quantitative skill: statistics grades, Python, R or SQL projects, or online certificates.
• Frame data as a business tool. Explain which business problems you want to solve, since the interview panel includes sector professionals.
• Choose Berlin or Madrid with a reason linked to your target market.
• Apply in Session 1 or 2 to leave time for visas in two countries.

Frequently asked questions

Does ESCP offer a Master in Analytics and Management (MAM)?

No. ESCP has no programme with that name. Its closest equivalent is the MSc in Business Analytics & AI, formerly the MSc in Big Data and Business Analytics: a 15-month programme taught in English in Paris and then Berlin or Madrid, with an internship of at least four months.

Do I need a maths or coding background for ESCP's analytics master?

ESCP lists no formal maths prerequisite or GMAT requirement, and students come from engineering, pharmaceuticals, literature and the social sciences. The curriculum covers machine learning, data mining and database management, though, so show the admissions team that you can cope with statistics and programming before you start.