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Data Scientist: Definitions and Job Descriptions in 2020

Today, data explosion is impacting global businesses. Demand for Data Scientists has rapidly grown, as enterprises want to obtain relevant insights from vast amounts of raw, semi-structured and unstructured data generated by connected devices.

Techopedia defines a Data Scientist as, “an individual, organization or application that performs statistical analysis, data mining and retrieval processes on a large amount of data to identify trends, figures, and other relevant information.”

Techtarget.com defines a Data Scientist as, “a professional responsible for collecting, analyzing and interpreting extremely large amounts of data. The data scientist’s role is an offshoot of several traditional technical roles, including mathematician, scientist, statistician, and computer professional.”

Read more: Best Data Analytics Tools for Business Intelligence Teams

Key Skills Required

On the technical side, data scientists should be well-versed with the knowledge of software languages – Python, Hadoop, R, Spark, SQL, SAS, Java, Matlab, Tableau and Hive. With AI and Data Analytics as the frontrunners for the future workforce, Python is a vital skill to learn. Additional skills include quantitative and experimental analysis along with implementing Machine Learning to scale up the organization’s data strategy.

Data Scientist: Job Descriptions in 2020

Here are the top 3 job descriptions that define the roles and responsibilities of a data scientist. Setting the right expectations is essential to achieve success in your career.

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1. The top job on Glassdoor is that of a Data Scientist, a position that won’t change in the future. The website’s job description states that a Data Scientist will support multiple teams – Sales, Product, Marketing, and Leadership by providing insights gained from the analysis of organizational data. Ideal candidates must be adept at working on huge data sets to identify business opportunities and using test models to study the effectiveness of different actions.

Candidates must have strong experience in using varied data analysis methods, tools, in building and implementing models, creating algorithms and running simulations. Proven capabilities in driving business performance with accurate data insights are essential. The candidate must be comfortable working with diverse functional teams and stakeholders.

2. The job profile on LinkedIn states that an ideal candidate must collaborate with Engineering and Product Design teams for the accurate needs assessment. Extensive research skills will benefit from devising statistical data analytics models. The candidate should communicate data insights to stakeholders enabling smarter business operations. Staying up-to-date about the latest technology and industry trends will help the Data Scientist to implement the latest analytical tools to generate relevant business insights.

3. Another job description reads, “We are looking for a Data Scientist who will analyze huge amounts of raw information to identify patterns in order to help improve our business processes. We rely on you to build products for extracting valuable insights. In this role, you must have deep knowledge of analytics, statistics and mathematics to develop highly analytical models. Skills of problem-solving and critical thinking will be essential for accurate data interpretation quickly.

Your passion for Research and Machine Learning will help us analyze market trends to make informed business decisions.

Big Data Courses in the US and UK are helping organizations gain a competitive edge. 

(How are you preapring for the AI age ahead. Share your insights with us at news@martechseries.com)

Read more: Skills to Become Microsoft AI Engineer

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