Today I’m going to talk to you about becoming a Data Scientist, which is a title that is emerging as one of the hot job prospects in coming years. If you are someone who likes to solve complex problems, can pull together data from a number of different disciplines, are good with information technology, maths, science, and fancy yourself as a trend-spotter, then data science might be just the thing for you!
Basically a data scientist is someone who pulls together data from an array of different sources and is able to analyze that data in a way that reveals patterns helpful to the company for business development, marketing, product development, and so on. Now that’s a rather broad definition and that’s because being a data scientist in any number of industries can be broad in terms of what is done. The key function of a data scientist is to take data and make it relatable for the business, to make it into a representation of patterns that the decision makers can look at and say something like “Hey, the sales trend is leaning into the teen market, let’s change our marketing to follow that trend more aggressively.” Or maybe the demographic data on your social media channels is swinging toward a particular age, sex, geographic area, education level, etc., and there’s parallels with a strong competitor’s marketing campaign and trending topics in the media. There are millions of data points that need to be organised, by highly advanced algorithms, and then put in some sort of visual or graphical representation that reveals this pattern. That’s the job of a data scientist. The billions of data points out there, what we know as “Big Data”, are often unstructured, overwhelming and to be honest, useless to informing business decision makers. What business needs is an interpreter – they need a data scientist!
Technical Skills:
  1. Data scientist will usually have a masters degree or even a PhD and so a strong academic foundation is needed.
  2. Typically you will get an undergraduate degree in computer science, social science or one of the physical sciences with a grounding in statistics. Then there will be a Master’s degree or PhD in data science or a related field.
  3. You will also need to have gained proficiency in an analytics tool like R ( that is used to solve statistical problems and manipulate data.
  4. You would also be skilled in a programming language like Python, Java, Perl, or C/C++. About 40% of data scientists use Python as their main programming language.
  5. Other skills such as familiarity with Apache Hadoop ( , Hive (, Pig (, and Spark ( – all tools to process and analyze large data sets, and cloud tools like Amazon S3 ( is also an advantage.
  6. Understanding machine learning and how artificial neural networks, reinforcement learning, and other machine learning techniques work will be a huge advantage to you.
  7. Once you have data that means something you will need to present it in a way that other’s can comprehend and that’s where data visualisation comes into play. Visualising data with various visualisation tools like Tableau, D3.js, Matplottlib, and ggplot will be important skills to have as a data scientist.
Other Skills:
  1. Naturally curious and a drive to want to find out “why” things are the way they are.
  2. Organized – You need to be able to organize data and results when handling lots of data points from many different sources.
  3. Critical thinker – It’s one thing to put data points on a chart it’s another thing to creatively and critically evaluate what it means and how it all fits together in the larger scheme of things.
  4. Focus – Working with data requires focused attention, often for long stretches of time, and an attention to detail without quickly getting board if the magical revelations don’t jump out at you immediately.
  5. Good communication – To get data, collaborate with others and communicate results to your employer, your communication skills need to be strong. To be able to communicate in a non-technical way to the company you are working for and give non-technical summaries and ideas of opportunities will be a key skill to have.

This is a career that is constantly evolving as more data becomes available and companies learn how to use it in more effective and creative ways. Just about every industry and every company in those industries use data and the interpretation of data to make business decisions and so the data scientist is at the heart of many companies. Companies are going to increasingly need someone to gather, organize, store, interpret and visualise important data that directly impacts the company, and these companies will pay handsomely for such people.
Work as a data scientist is often in a office-like environment where you collaborate with others on projects. Obviously the atmosphere, pace and work conditions will vary depending on the industry and company you work for, but your skills as a data scientist are very much transferable across companies and industries. Some work environments will encourage creative thinking and problem solving and others less so, wanting just efficient “number crunching”.
Job satisfaction will likely revolve less around pay rates (you are likely to be paid well) and more about your interest in what the company does, the capacity to be creative, and the pace and feel of the work environment. There will be opportunity to specialize and become senior in a particular area of your work your find interesting and rewarding and this will, in turn, be financially rewarding as well.
A career as a data scientist will mean you are continually learning new systems, software, techniques. You may find last year’s efforts to learn a particular platform are suddenly obsolete and you have to learn a new platform or tool this year. You will need to be comfortable with a work landscape that is in constant flux and love learning new things all the time.
The prospects for employment are good and increasingly so in the near-term as there is a shortage of data scientists at the moment. You can expect to be earning well over the national average and the job is likely to become increasingly valuable as time goes on and companies rely more strongly on good data analysis.
The estimated salary for a Data Scientist varies across industries and countries, with reports in Australia of averages in the $90K/year mark, and the Burtch Works Study ( reporting anywhere between $95K-$250K depending on experience and status. Salary site PayScale ( put data scientist around the $92K/year mark in the USA.

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