Data Scientist Job Description: Everything you need to know

Today, we’re covering the data scientist job description — what is a data scientist, what does a data scientist do, the qualifications for a data scientist, the data scientist roles and responsibilities, data scientist skills, how to be a data scientist, data scientist requirements, and the data scientist career path. 

The data scientist is a relatively new key player in organizations — a new breed of analytical data experts. It involves being part mathematicians, part computer scientists, and they rule the world of big data. Businesses today are wrestling with volumes of unstructured information that’s a virtual gold mine, which can help boost revenue when unearthed. But they really need professionals who can dig in and find valuable business insights, sifting through the useless chaff and finding the precious nuggets of data. That is what data scientist does; that is why they are highly sought after and well paid. 

Data Scientist Job Description

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Organizations are rapidly using more and more data in their everyday operations. A data scientist interprets the raw data and extracts valuable meaning out of it. They then use this information to find patterns and develop solutions that an organization needs to grow and compete. 

If we must define a data scientist, it would be someone who makes value out of data. Wondering what exactly constitutes the job of a data scientist? Well, no points for guessing, a day of a data scientist revolves around – as the job title suggests – data and data everywhere.  

The data scientist job description involves fetching information from various sources and analyzing it to get a clear understanding of how an organization performs. They use statistical and analytical methods plus AI tools to automate specific processes within the organization and develop smart solutions to business challenges. After interpreting the data, they present the results in a clear and interesting way. The objective is to help the organization analyze trends to make better decisions. Thus, a good data scientist needs to have the right combination of technical, analytical, and communication skills. 

In order to understand the data scientist role, let’s first understand that the data scientist position has evolved and expanded from the data analyst job position. 

Both the data analyst and data scientist organize and analyze big data within an organization. But the data scientist has the additional role of using business sense and communication skills to influence how the organization tackles business challenges. 

Data scientists combine practical skills like coding and math with the ability for statistical analysis to achieve results. For instance, a data scientist working for a social networking site might analyze the types of pages users ‘Like’ and, based on that, decide what kind of advertisements users will see upon logging into their account.

Data Scientist Roles and Responsibilities: What Does a Data Scientist Do?

Data scientist roles and responsibilities include:

  • Data mining or extracting usable data from valuable data sources
  • Using machine learning tools to select features, create and optimize classifiers
  • Carrying out preprocessing of structured and unstructured data
  • Processing, cleansing, and validating the integrity of data to be used for analysis
  • Developing prediction systems and machine learning algorithms
  • Presenting results in a clear manner
  • Collaborate with Business and IT teams

Data Scientist Skills

You need to master the skills required for data scientist jobs in various industries and organizations if you want to pursue a data scientist career. Let’s look at the must-have data scientist qualifications.  

Key skills needed to become a data scientist:

  • Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig are desirable. Familiarity with Scala, Java, or C++ is an added advantage.
  • Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies. 
  • Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests. 
  • Strong Math Skills (Multivariable Calculus and Linear Algebra) – understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques. 
  • Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist\’s job description. 
  • Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., The tableau that helps to visually encode data
  • Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
  • Strong Software Engineering Background
  • Hands-on experience with data science tools
  • Problem-solving aptitude
  • Analytical mind and great business sense
  • Degree in Computer Science, Engineering or relevant field is preferred
  • Proven Experience as Data Analyst or Data Scientist

How to Become a Data Scientist

If you are wondering how to get hired in a data scientist role, then it is best to know that such lucrative jobs do not simply fall out of the sky, it takes time, effort, and knowledge.

To pursue a data scientist career, you have to devote time to learn data science, upgrade your skills, search for a job and prepare for interviews. Simplilearn’s Data Science Certification Courses offer an excellent way to learn all the skills we discussed here. 

Consider these to start your career as a data scientist.

  • Be Patient: you will apply for several jobs before bagging one
  • Build up Data Analytics, Programming, and Business skills. 
  • Be prepared to answer data science interview questions about how you would behave in various work situations. Remember, recruiters, are more interested in how you solve problems and how you tackle specific situations than your technical knowledge.  
  • Consider earning a certificate in Data Science or Business Analytics 
  • Create a portfolio to showcase some projects that you have done with real data

How Much Does a Data Scientists Job Pay?

The demand and salary for data scientists tend to be higher than most other ITES jobs. Experience is one of the key factors in determining the salary range of a data science professional. 

According to Glassdoor, a Data Scientist in the United States earns an annual average of USD 117,212.

Data Scientist Career Path

Data Science is currently considered one of the most lucrative careers available. Companies across all major industries/sectors have data scientist requirements to help them gain valuable insights from big data. There is a sharp growth in demand for highly skilled data science professionals who can straddle the business and IT worlds. 

The career path to becoming a data scientist isn’t clearly defined since this is a relatively new profession. People from different backgrounds like mathematics, statistics, computer science, or economics, end up in data science. 

The options for data scientist careers are quite varied. Since data science is a multidisciplinary profession, there are exposure and exit options in numerous areas. 

The major designations for data science professionals are:

  • Data Analyst
  • Data Scientist (entry-level)
  • Associate data scientist
  • Data Scientist (senior-level)
  • Product Manager
  • Lead data scientist
  • Director/VP/SVP

That was all about the Data Scientist Job Description.

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