In a competitive job market, technical skills alone are not enough. Kick-start your analytics career with our integrated Masters in Analytics and Management, developing applied data methods and modelling alongside the sought-after global business mindset recruiters now demand.
The MAM combines London Business School’s superb reputation and world-class faculty in general management with cutting-edge data analytics. Future-proof yourself. Bridge the gap between data and effective business solutions.
MAM students are numerate, ambitious individuals in the early stages of their career. With a keen interest in data analytics, you’ll develop programming and technical ability, sound business acumen and a robust toolkit of soft skills to help you advance your career.
Showcasing a strong understanding of business fundamentals, graduates from MAM are likely to excel in a Business or Data Analyst role. You’ll have the potential to work across a wide range of sectors and the skills to take on broader business strategy responsibilities. So whether your interest is in consulting, technology, finance, retail or healthcare, you’ll secure the relevant competencies to kick-start you career and progress to higher, value-added roles.
MAM students must have a strong degree in a quantitative subject such as Engineering, Maths and Sciences, Computing, Economics, Accounting, Finance or Business and Management. Alternatively, you should be able to demonstrate clear proof of your quantitative ability.
As a MAM student you’ll join our dynamic and growing Early Careers community. Outstandingly global, students from these programmes are 95% international and currently represent over 50 different countries. And, at last count, our diverse network of more than 43,000 alumni spans 155 countries around the globe.
Check out class directories for our current Masters in Management (MiM) and Masters in Financial Analysis (MFA) programmes, to see just how high-calibre your new MAM classmates will be*.
* As the first MAM class will launch in August 2019, there is currently no directory specifically for this programme.
Making the right choices early on in your career is vital for future success. Cutting-edge and highly applied, the MAM curriculum has been developed in close consultation with top recruiters, ensuring you meet the requirements for skilled graduates who combine strong data analytics skills with sound business acumen.
Our dedicated Careers team will support you throughout your MAM journey. They’ll prepare you for tough interviews, and develop your core toolkit of professional skills through one-to-one sessions, lectures and online training. 96% of our MiM2017 graduates accepted an offer within three months of graduation*; we expect our new MAM graduates to hit the ground running, entering sought-after sectors like technology and consulting with similar levels of success.
To see where our most recent Early Career MiM and MiF graduates are now, download our latest employment reports.
* As the first MAM class will launch in August 2019, there is currently no employment report specifically for this programme.
Designed specifically to produce high-calibre graduates who can deliver business impact through analytics, MAM offers a unique curriculum targeting the intersection of business, data science and machine learning.
Our broad analytics core is supported by a comprehensive programming and database curriculum. Receive training in R, Python, Tableau, SQL, Excel and other data-related software and take part in exciting initiatives like Hackathon. Immerse yourself in a live company project using real data to tackle a real business problem. Throughout, you’ll build a robust business toolkit, and benefit from our proven, global expertise in management education.
You can extend your Masters in Analytics and Management to a fourth term and pursue the option to take three additional elective courses or go on an international exchange with a top business school. The option to take a fourth term is contingent on your career track, and is subject to additional fees.