10 DATA SCIENCE SKILLS YOU NEED TO GET HIRED!

For those of you who are new to Data Science, it is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining. If you have an interest in mathematics, technical and programming skills, business and strategy awareness, then Data Science is the field for you!

However, if you acquire certain skills, then this field will become easier and even more successful for you.

Coding Skills

This is one of the most basic requirements for a data scientist, irrespective of which industry or company you plan to apply for. It is expected from a data scientist to have sufficient knowledge of languages such as Python, C++, Java, Scala, Clojure, Java, Octave etc.

Programming

It is a primary skill if you want to make your career in data science. It is essential to have knowledge regarding critical parameters like debugging and compiling, testing and implementation etc.

Machine Learning

If you aim to work at companies that churn huge amounts of data like Google and Netflix, then having a basic idea of Machine Learning will go a long way. You can learn about k-nearest neighbours, random forests, ensemble methods etc.

Statistics

As a data scientist, you should familiarize yourself with basic concepts of statistics like statistical tests, distributions, maximum likelihood estimators, etc. This helps in the management of any solution, and it’s the approach.

Calculus and Algebra

Since calculus and algebra play an important role in determining minute improvements in predictive performance or algorithm optimization and superior techniques, it is an advantageous skill.

Data Wrangling

Data will never come to you in an organized form, so it’s better to be a data proof-reader. You should be proficient in spotting mistakes in missing values, inconsistent string formatting, date formatting, Unix time vs timestamps, etc.

Data Visualization

Your competence in data visualization tools like matplotlib, ggplot, or d3.js will be of value because of visually encoding data and communicating information is a primary requirement when you’re in data science.

Software Engineering

You will be an asset to any company if you have a strong software engineering background. It will help you to and handle any data-driven projects as your culminated skills will be useful in a project.

Apache Spark

Even though it’s not a necessity, awareness of Apache Spark will be helpful. It is specifically designed for data science to help run its complicated algorithms and large sets of data a lot faster.

Data Wisdom

As a data scientist, you will be expected to have sound knowledge of the decisions an employer might want to take, it’s consequences and benefits. Business acumen proves very handy at some point or the other.

Other than these skills, having a general awareness of data science developments is necessary to keep yourself up to date. One needs to have excellent communication skills and be a team player because any data science project is not the work of one person, instead, there are multiple people at different tiers who work together to create something remarkable!