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Home / Blog / Artificial Intelligence / Data Scientist vs Artificial Intelligence Engineer?
Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of AiSPRY and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 18+ years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.
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A data scientist is someone good at both mathematics and computer science. They bridge the gap between the business and IT sectors, are in high demand, and earn well. It would be a surprising fact that data scientists have paved the way for themselves only in the last couple of decades. Companies did not realize the importance of data scientists until big data was fully understood. Today, data scientists are the most sought- after and in high demand. According to Harvard Business Review in 2011 the job of a Data Scientist is renowned as ‘the sexiest job of the 21st century’. Earlier, data science was included as part of statistics in mathematics. Data science as a field gained recognition only after the world thoroughly understood the significance of data science in every area.
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What does a data scientist do?
Using statistical tools in mathematics and analyzing data for making informed decisions is the prime goal of every data scientist. A data scientist is someone who uses algorithms, math, statistics, design, engineering, communication, and management abilities to extract valuable and practical insights from vast volumes of data and positively influence the use of algorithms, math, statistics, design, engineering, communication, and management abilities to extract valuable and practical insights from vast volumes of data and have a beneficial influence on the company.
To extract meaning from data, data scientists make heavy use of statistical techniques, distributed architecture, visualization tools, and many data-oriented technologies including Hadoop, Spark, Python, SQL, and R. Data scientists utilize the information they collect to inform different business processes, analyze user metrics, forecast potential business hazards, evaluate market trends, and improve decision-making to achieve organizational objectives.
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Objectives of a data scientist:
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An average data scientist makes $139,000 a year.
The US Bureau of Labor Statistics reports that there is a significant need for data professionals, with statistics and mathematical science employment predicted to expand by 31% and 33%, respectively, between 2020 and 2030. (BLS)
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In order to become an efficient data scientist, it is important to upgrade one's knowledge in some areas like Programming languages, Machine learning, Big data, Data visualization, and Communication.
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The one-man army of artificial intelligence developers is responsible for transferring human intelligence to machines, from creating a robot hand to solving Rubik's cubes to speech recognition systems. An organization's AI applications and systems are created, implemented, tested, and maintained by an artificial intelligence engineer. In addition to having a solid working understanding of the field of artificial intelligence, this calls for programming and statistical analysis. The creation of clever autonomous models and their integration into applications are tasks for an artificial intelligence engineer. Building, maintaining, and deploying end-to-end AI solutions is done by AI engineers using machine learning, deep learning, software engineering concepts, algorithmic calculations, neural networks, and NLP. To develop AI solutions that may enhance operations, service delivery, and product creation for corporate profitability, they collaborate with business stakeholders. At some companies, artificial intelligence engineers are more research-oriented and focus on developing the best model to solve a problem while developing, deploying, and training AI systems.
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What skills should an AI engineer possess?
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According to Pay Scale, an artificial intelligence engineer's salary is 1,500, 641 lakhs per annum in India.
So, it is evident that data scientists and AI engineers are quite different and have different responsibilities. It is however necessary to remember that a data scientist creates data products that support successful corporate decision-making, and an artificial intelligence engineer assists firms in creating unique solutions that deliver autonomy. Data scientists and AI developers collaborate closely to develop solutions that clients can use.
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