Getting the Most Out of Your Data Science MSc

Getting the Most Out of Your Data Science MSc

This guest post comes from Leslie Salami, data scientist and data engineer at Nalytics, and joint runner up at last year’s e-Placement Scotland ‘Placement of the Year’ Awards.

Leslie shares his advice to data science students on getting the most out of their course and that all-important Data Lab industrial placement.


I come from a strong technical background. Before undertaking my MSc, I worked as a software engineer and then worked my way up to become a solutions architect.

You guessed right - I have a Bachelor of Science degree in Computer Science.

What I Do

I work as a data scientist and data engineer for Nalytics. Nalytics is a unique cloud solution for extracting knowledge from all of your unstructured data from any device.


Nalytics helps individuals, teams and entire organisations access and analyse their data to enhance insight, drive innovation and deliver improvements. My current role involves adding and improving the AI capabilities of the Nalytics platform.

The main languages I work with are Java and Python.

How to Get the Most Out of Your Data Science Course

I studied MSc. Big Data at the University of Stirling.

My advice to all students is to have the mentality that the lecturers are not there to teach you everything. Their role is to give you a strong foundation in each area of Data Science, to enable you to improve your data science skills on your own.

The best students always go outside their comfort zone and try and learn new things outside what has been taught in class.

How to Get the Most Out of Your Placement

An important element of my MSc was my Data Lab industrial placement. Industrial placements allow you to have hands-on experience in a real working environment with real data.

The MSc programme provided me with the knowledge and techniques to tackle big data problems, but the placement at Nalytics gave me the opportunity to actually implement a solution within the corporate environment working on a real project.

My advice is to take on a project that allows you to market yourself to the company you undertake your placement with, as well as other companies.

Leslie receiving his award

A very good way of ‘selling’ your data science skill-sets to a potential employer during an interview is to be able to showcase a data science project that you have worked on. This is one of your key selling points. Your industrial placement gives you an opportunity to build those all-important skills.

“As a start-up technology company, it was extremely useful for us to use the industry placement programme to prove our technology (in terms of integration, scaling and extensibility) on real-world big data challenges…Leslie’s project deliverables are already being utilised by our business when demonstrating the product to potential customers.”

David Rivett, Nalytics COO

Things I Wish I’d Known About When I was Studying

One of things I wish I had known when I was studying is that Data Science is a really broad field!

You cannot have a strong command in every aspect of it. It’s better to be have a well-rounded understanding of data science as a whole and then find an area that you want to specialize in.

Employers know that building your skills takes time and that you’re not going to become the ‘finished article’ in the course of your studies. They also know that the skills you’ve built over your MSc year can be applied in different contexts. For example, once you have the skill to train a model, evaluate and deploy a model for an NLP project, you can definitely apply the same skills to a FinTech project.

Connect with Leslie via LinkedIn.