Forget gold, diamonds, oil (and Bitcoin?) – the world’s most valuable asset is data. While the value of other assets has seesawed in recent years, the value of data continues to rise, maintaining its 10% year-on-year growth, expected to hit over £340 billion by 2026.
Data Scientists are on the front line of this enormous opportunity. But what does a Data Scientist actually do?
Data Scientists use raw data to predict future trends. To do this, they deploy a mix of quantitative and qualitative skills that derive insight from data, and then communicate these insights across their organisation. They create models, clean data, develop Machine Learning algorithms, collaborate with teams, tell stories (based on their models) and refine their thinking…again and again.
Great data scientists are constantly zooming in – to the most granular level – and out – to see the bigger picture. They are deeply analytical, great communicators and outstanding problem solvers.
Data Scientists need to be BOTH highly quantitative and highly qualitative.
Highly quantitative skills include:
Maths & Statistics, including Machine Learning, Statistical Modelling, Experiment Design, Bayesian Inference, Supervised Learning, Unsupervised Learning & Optimisation (Gradient Design & variants)
Programming & Database, basic of Computer Science, Python, R, SQL / NoSQL, Relational Algebra, Parallel Datasets & Parallel Query Processing, MapReduce Concepts, Hadoop, Hive/Pig, Custom Reducers & XaaS (i.e. AWS).
Highly qualitative skills include:
Communication, including Storytelling, Translate Data-Driven Insight into Decisions/Actions, Visual Art Design, Visualisation Tools (i.e. Tableau, D3, Flare).
Domain Knowledge / Soft Skills, including Business Understanding, Business Curiosity, Ability to Influence without Authority, Problem-Solver Mindset, Strategy, Creativity, and Collaborative.
Want to get a deeper appreciation of the type of projects you’re likely to encounter as a Data Scientist? These sites are critical tools for Data Scientists.
Dataset Search by Google
CoLaboratory by Jupyter
As a Data Scientist, CVs matter less than the projects you’ve worked on and the problems you’ve solved. Therefore, you need to be able to showcase your work in a different format. Portfolios are becoming increasingly popular with tools like Biolink, Limey.io and Linktree being used by Data Scientists to exhibit their past and current projects.
Included below are the average salaries (USD) for Data Scientists across the top paying countries in the world. Please be advised there are big variances in each country depending on seniority.
1. USA: $115,994
2. Germany: $115,027
3. Australia: $109,178
4. Netherlands: $105,249
5. France: $105,139
6. Canada: $101,299
7. Sweden: $100,241
8. UK: $92,760
9. New Zealand: $89,704
10. United Arab Emirates: $82,552
Thanks to Salary Expert for this data.
Data Science is one of the most exciting industries today, one that is only set to grow.
If you’re looking for roles in data science or other Deep Tech areas, check out these opportunities with some of the most inspiring companies in the world.