In LSE Careers we meet an increasing number of students seeking to enter the Data and Tech sector, coming from a wide range of academic departments and degrees, and with a common interest in technology and analytics.
Not surprisingly, we also meet more and more employers seeking highly analytical students and graduates with strong quantitative skills, to help them apply data analytics to business decision making, in organisations ranging from big corporate companies to startups to tech companies to consultancies, to the public sector.
In this post we’ve listed a number of resources to help you to find jobs and internship vacancies, prepare technical interviews, find information on specialist websites or blogs, find resources to develop your technical and analytical skills or gain experience via projects, and some other useful coding tools.
We’ve gathered this list over the past weeks, thanks to employers and LSE alumni who participated in different events such as the Careers in Data and Tech week taking place in March and shared their preferred tips and tools with the audience, and thanks to the precious contribution of the Digital Skills Lab.
Job boards are a good way to understand what roles are out there in the tech sector, or tech roles in any sector, and what are the trending skills required. Dice and Hired are very popular, and a good place to start. For jobs in start-ups, we’d recommend AngelList, which presents itself as a startup ecosystem, and Work in startups with jobs mostly based in in the UK. We’d also like to highlight Otta, advertising jobs and internships in fast-growing companies, from startups to tech giants, and Weareunbox, offering project-based internships at startups, accelerators and VC funds, with applications to be made via video pitch and written questions. Finally, Jumpstart are a start-up graduate programme for non-tech roles. You can watch their presentation at LSE here.
Specialist websites, blogs and podcasts
There is a large amount of resources you can access to increase your knowledge about data science, data analytics, programming languages, and future trends. Alongside with the events series of the LSE Data Science Institute and the LSE SU Data Science society, here are a few of them we came across:
- exponentialview.co, a podcast by Azeem Azar
- towardsdatascience.com and medium.springboard.com, two blogs on data science
- Dataquest’s blog offer tutorials for learning data science techniques and technologies
- Monkeylearn focus on sentiment, intent and keywords analysis and have a blog
- Kaggle gather a community on machine learning and data science, offer free courses, share public datasets and organise competitions and have a blog too
- for blogs, news tutorials on R and Python, you can go to rweekly.org, r-bloggers.com and pycoders.com.
Online courses to develop your technical skills
The LSE Digital Skills Lab are a great place to develop your technical and coding skills and to find a list of resources, online courses and workshops.
We’re highlighting below a few online courses we came across (all of these websites offer free courses): Founders and Coders, codeatuni.com, open.edu/openlearn/science-maths-technology/make-changing-world-better-place (courses on topics such as Internet of everything, ICT systems, cyber-security, themes and theories for working in virtual project teams, software and the law). Lambda School is also amongst the most popular online coding schools.
Other courses and tutorials include:
- w3schools.com (tutorials on a variety of programming languages)
- overleaf.com/learn/latex (on how to learn LaTeX, the typesetting language)
- bigbookofr.com are an online book with links and descriptions of all the open-source and freely available R courses and tutorials (there are a lot)
- data-to-viz.com help you to learn the most appropriate graph for your data;
- r-graph-gallery.com and python-graph-gallery.com feature hundreds of charts made with either R or Python, which include step-by-step guides and code
- Finally, https://projecteuler.net/about are worth mentioning as they list a series of challenging mathematical/computer programming problems that will require more than just mathematical insights to solve. The use of a computer and programming skills will be required to solve most problems. As they describe themselves, they wish “to provide a platform for the inquiring mind to delve into unfamiliar areas and learn new concepts in a fun and recreational context.”
Gaining work experience
The Forage offer virtual work experience programmes where top companies teach students the skills they hire for.
Polymath provide collaborative research projects to undergraduate students who wish to develop their mathematics skills.
Datagrasp advertise term-time project opportunities with advanced analytics, data science and data engineering skills.
Preparing for technical interviews
HackerRank have a platform with coding tutorials and practice problems, along with interview preparation challenges and tips.
Coderbyte have listed the best coding challenge websites, which are a great way to prepare for coding interviews.
InterviewCake offer advice on technical interviews and list programming interview questions and how to solve them.
Tools to work on and share coding
We are listing here a few interesting collaborative tools. Beyond Github’s development platform, you can also use: the Jupyter Notebook, an open-source web application that allows you to showcase your work; Colaboratory, Google’s tool to write and execute Python coding; R Markdown, an open source notebook interface to weave together narrative text and code to produce elegantly formatted output and using multiple languages including R, Python, and SQL; Shiny, an open source R package that makes it easy to build interactive web apps straight from R.
Hackathons and networking events to engage with the tech community
The Digital Skills Lab with LSE Careers are organising an annual Python Coding Challenge in Lent Term, to develop and apply coding skills to a real-world problem suggested by an external organisation. The challenge is open to LSE students from any degree programme, and is a wonderful way to meet peers from different backgrounds and sharing similar interests.
To engage with the start-up and innovation world at LSE, Generate offers a lot of networking opportunities and events with entrepreneurs.
Beyond LSE, London is one of the biggest tech hubs in the world, and there are a lot of London meet-up groups in the tech sector. On meetup.com you can find a list of groups dedicated to different areas of the tech field and identify online events you’d like to attend. You can also choose other locations than London or the UK.
Getting involved in hackathons is a good way to meet other likeminded people and work together on projects. Hackerearth lists upcoming hackathons in London and other cities; Eventbrite also lists hackathons and other upcoming events, including a range of free events.
And finally, Makeover Monday and Tidy Tuesday offer weekly social challenges shared online and via social media. Each week you’re given a dataset and a challenge to analyse and visualise, sharing your output with the community for feedback and ongoing learning – this is also a great way to develop a portfolio of work.
In addition to these resources, we’d encourage you to have a look at the recordings or slides of some of the presentations and panel events that took place over the past year about the data and tech sector, and at the Data, Information and Technology employment sector page.