Data Science skills for software developers

by Amrendra Lala on Tuesday 3 April 2018, 4:50 PM | Category: Marketing Management| View: 562 views

Data Science is an interdisciplinary field of scientific methods, systems, and processes which helps in extracting knowledge or insights from data. This subject is also known as Data-driven Science. The data mentioned here may be structured or unstructured. The unstructured data may take various forms like texts, images or videos. It is also the responsibility of the data scientist to help make the business decision. They help to analyze data and present it in a way that can help make business decisions. It can be said that Data Science is simply the conversion of data to knowledge.

Data scientist and software developers work on the different parts of the same workflow. It is the function of the data scientist to analyse the data for new insights. The software developers, on the other hand, use these insights to create new apps. So, it can be said that both of them work towards the common goal of creating well-structured apps. So a close collaboration between them is required to bring success in business. In this article, the Data Science skills which a software developer must possess to successfully run the show would be discussed.

Data Science Programming Languages

A software developer should possess good knowledge of the different programs used by the data scientists. Python, Perl, C/C++ and R are the most common computer programs used by the data scientists. There are also many add-on applications like Numpy, SciPy, Scala used in Data Science.



In order to perfect the Data Science skill, the software developer should have a good knowledge of mathematical calculations and at least a basic knowledge of multivariable calculus or linear algebra. This is very important because in this business the product is defined by data. A small improvement in predictive performance can create a huge difference in the business results.


Data Mining

The software developer should also have some basic knowledge of data mining. This includes skillful conversion of messy or imperfect data into a managed set of data. Dealing with a large amount of data can be messy at times. A software developer should be able to manage missing data, inconsistent string formatting, and date formatting.



A good knowledge of statistics is also important for a software developer to bring success in Data Science related business activity. He should be well versed in statistical analysis, exploratory analysis, and predictive analysis and would be able to identify and apply the appropriate algorithms to the data. He should be familiar with the use of statistical tests, maximum likelihood estimators, distributions, etc.


Machine Learning

When a software developer works in a big data-driven company where he is required to deal with terabytes or petabytes of data on a daily basis, a good knowledge of machine learning skill is a must. The machine learning methodologies and techniques would be a great help to him in his everyday problem-solving activities. It is better if you have a sound knowledge of random forests, k-nearest neighbours, and ensemble methods.


Analytical Skills

A sound knowledge of analytical skills can be of great help to the software developer when his business makes him deal with large volume of data. Knowledge of mix modelling, attribution modelling, user profiling and segmentation, retail optimisation and calculation of long-term value is beneficial for his job. SAS, Hadoop, Pig, Spark, and Hive are the important data analytical tools that are often used by the software developers as well.


Communication Skills

The software developer should possess' good communication skill as well. It would help him to listen to everyone involved in the business and take the right decision in problem-solving activity. The communication proficiency must cut across all digital platforms like SMS, conference calls, etc this would make him stand out in Data Science related activity.

 The above was in brief, the important Data Science skill required by a software developer to achieve success in his profession.

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