If you are looking for a career as Data Scientist and need to know data scientist job description, we are Here to assist you on finding the required skill set for a Data Scientist Profile as per company’s data scientist job description available. Data Science is in trend and Data Scientist is the one of the Sexiest Job in 21st Century as per so many article published in recent days. High Salary and fun in job makes it so popular among Technical guys. I mean, I have also included you as well in this list. Every Data Scientist must have these skills to fit them self in Good Companies whether a Fastest Growing Startup or Big MNC.
Data Scientist Job Description
Every job Description is consisting of two sections which are – qualifications for data scientist and second is their Responsibilities. So in this article we will discuss each one by one, we will also help you to find best data science programs available in the Market.
Qualifications for Data Scientist
By using the word qualification, we do not mean to mention Degree required for Data Scientist. We have the concern of Skills, So Every Data scientist must have excellent understanding of
- Data Mining Machine Learning – Machine learning data mining is at the top in the term of skill requirement for a Data Scientist in Data Scientist Job Description. This area covers algorithms like SVM, Decision Tree, K-nn, Naive Bayes etc. with their implementation. If you want to learn these algorithms, you can refer books – Machine Learning for Dummies .
- Expertise in Data Science Tool- Data Scientist should know two type of tool one is basic data science tool like – R, Weka, NumPy etc. along with it They should also know some Visualization tool like – D3.js, GPlot etc. These tools may be considering as ABCD of Data Science.
- SQL and No SQL Both Database quires are important – Extracting the Sense out of that Data and make it Meaningful is Primary focus of Data Science. Here We have to deal with both Structure and Unstructured Data that’s why we need basic understanding of both database (SQL and NoSQL). For better understanding of NoSQL database, you can refer these link – NoSQL Training and Tutorials.
- Programming Language Knowledge for Data Science is a Plus – If you want to make your own classifier, you definitely need to write some code, here you need the knowledge of some programming language. Now you will ask which one so the answer is,” It Depends on the system for which you are writing the code as an extension of System. If it is in java you should go for java because Integration will be easier. You can also use other compatible programming language which may fit in your architecture. Python and R is more recommendable than Java for data Science and machine learning modules because there are more libraries and pre ready code set in Python and R in comparison of java for development.
You may refer these link for leaning these skill- Pyhton
- Statistics and Proficiency in Mathematics – Perfection in numeracy is one of the most important factor in career of Data Scientist as per Data Scientist Job Description. I mean it is required in every phases of Prediction and building Model with pattern recognition.
- Big Data and Natural Language Processing
Big Data Business Intelligence is a hot topic in every industry. Big Data Business Intelligence is used to predict different parameters in different domain. It also creates some confusion that Big data engineer are same like data scientist, yes there is quit overlap but these two are completely different and have different responsibilities. Big Data Business Intelligence is a complementary skill for data scientist.
Now It’s Time to explain the Role of a Data Scientist as per Data Scientist Job Description available from the researches and surveys over many Companies.
- Data Science for Business and predictive analysis is based on the domain information of the business for which the data mining projects are done. So Every Data Scientist must have enough understanding of the domain on which data mining projects are carried out by the firm.
- Data Scientist is supposed to implement new machine learning module to existing system or to enhance the accuracy of existing data mining machine learning module or data mining projects of the firm.
- Data Scientist is supposed to integrate various results from big data business intelligence modules in addition to data mining projects.
- Every Data Scientist are supposed to model data and need to apply different queries on different data mining projects as per application of data science for business.
Data Scientist must be able to work on visualization tool to present the results in user friendly way which he gets from big data business intelligence modules.
Hidden Facts about Data Scientist Job Description:
Every job description contains some hidden features which are called silent features, So Data Scientist Job Description is no more an exception, it also contains some exciting silent features like:
- Prior Experience in Big data business intelligence.
- Work experience is also required in Data Mining Machine Learning projects.
- A Good level understanding of Mathematics is required as well.
- Innovation. “This is understood J “.
I think you must have got better understanding of Data Scientist Job Description. The Market is very high for Data Scientist job in almost every country in different Industry. If I talk about average experience of desired candidate in Data Scientist Job Description is at least 2 year Relevant and total 6 years in related field like Big Data Business Intelligence and Data Mining Machine Learning. Hey I know after having this long conversation on Data Scientist Job Description and Big data business intelligence you are excited about the salary. So you need to wait more for this, the average salary of a Data Scientist is location dependent as it happens in every profession. I can show you a global view from Glassdoor website
Salary is about $113436 in United States. For More information, please subscribe our website and stay in touch. You can also comment and ask related doubt through comment.