Ví dụ về việc sử dụng Data scientists trong Tiếng anh và bản dịch của chúng sang Tiếng việt
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This is the 1 choice for data scientists.
Data Scientists earned on average $128,240 in 2016.
Data scientists' salaries depend greatly on the region in which they live.
Of machine learning developers and data scientists now use Python.
No wonder, data scientists may be considered to be the hottest job of 21st century.
Companies in the present are facing a huge shortage of data scientists.
Languages used by data scientists often include SQL, R, and Python.
Lean on the new marketing lieutenants: marketing technologists and data scientists.
Data scientists are relatively new to the tech scene, but have quickly become the hottest job in America.
Possession of Big Data tools like Hadoop, Mahout,and Spark will increase the value of data scientists.
A great many data scientists are very strong engineers but feel like impostors when it comes to statistics.
Watson Studio provides a suite of tools and a collaborative environment for data scientists, developers and domain experts.
There are Data Scientists who fine-tune the statistical and mathematical models that are applied onto data. .
In 2018,LinkedIn's Singapore Emerging Jobs Report noted that data scientists grew 17x more within the last 5 years.
Many statisticians, data scientists or data analysts have at least a bachelor's degree in statistics.
Anjul Bhambhri, vice president of big data products at IBM,has described data scientists as"part analysts, part artists".
Data scientists typically are expected to have some fluency in at least one programming language-- Python and R being the favorites.
Miller and John Eysman pointed out in their answers,it is rare that data scientists need to implement machine learning algorithms from scratch.
In the next decade, data scientists will see a much greater distinction between senior data scientists and other positions.
The role of an analytics manageris to help guide a team of analysts and data scientists towards achieving their objectives and goals.
In the near future, Data Scientists will have the ability to take on areas that are business-critical as well as several complex challenges.
Digital marketing teams are usually composed of non-technical people that often rely on developers,designers, and data scientists to implement their ideas.
They are responsible for communicating data scientists about business goals so that they can work accordingly to achieve the objectives.
These professionals may vary in their skills and are likely to consist of software developers,computer scientists and data scientists.
This is one reason that data scientists are often responsible for developing machine learning components of a product.
For bridging this skill gap, IBM will align educational institutes withindustries to create a work-study environment for burgeoning data scientists.
Data scientists now have increasing amounts of data to prepare, analyze and group- and from which to draw conclusions.
Data scientists analyze secure transaction data collected from over 2 billion cards to get insights on revenue performance at a street level.