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#Data Science
“I think of data science as more like a practice than a job. Think of the scientific method, where you have to have a problem statement, generate a hypothesis, collect data, analyze data and then communicate the results and take action…. If you just use the scientific method as a way to approach data-intensive projects, I think you’re more apt to be successful with your outcome.” ―Bob Hayes, Ph.D, Chief Research Officer at Appuri
The discipline of data science or data-driven science shares similarities with data mining, and involves scientific methods, systems, and processes which extract information from different types of data. It lays emphasis on the source of information, what it signifies, observing patterns, and use of information as an imperative resource that aids conception and implementation of IT and business strategies.
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Data science amalgamates algorithm development, data inference and technology to offer solutions to analytically complicated problems. Additionally, it borrows substantially from computer science, information science, machine learning, statistics, mathematics and other fields which are cited below.
Data science amalgamates algorithm development, data inference and technology to offer solutions to analytically complicated problems. Additionally, it borrows substantially from computer science, information science, machine learning, statistics, mathematics and other fields which are cited below.
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Mining a vast amount of structured and unstructured data assists organizations in aspects of cost control, enhancing efficiencies and recognizing business opportunities that afford a competitive edge. With data at its core, ultimately, this science focuses on utilizing extracted data in stupendous ways to increase business value by aiding processes like decision making, trend analysis, product development and forecasting.
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Today, tech companies around the world seek brilliant data scientists who can proficiently extract beneficial information from stored, managed, and consumed data. To qualify for junior and senior positions in this sphere potential candidates are required to be well versed in the following:
Programming skills (degree in information and computer science with vast experience in Python, Perl, C++, Java, Hive, Tableau, Spark, Matlab, R, SAS, Hadoop, SQL or other database programming language)
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Statistics and Mathematics
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Machine Learning (understanding appropriate use of technology and broad strokes and Deep Learning)
Data wrangling or Data munging (data mining, classification and data analysis)
Data Visualization and Communication
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Data Intuition (data exploration analysis and insights)
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Business Acumen (for business analysis, predictive analysis and predictive modeling)
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Cluster Analysis (classifying and analyzing both structured and unstructured data)
Capable data scientists who dexterously deliver results using the skills mentioned above are hired to meet mutual goals in the following positions:
Aviation Data Analyst
AVP Data Scientist
Data Analyst
Data Analyst Automation Platform
Data Science Engineer
Data Scientist
Data Scientist – AI/ML/IoT/R/Python
Data Scientist Insight and Growth
Lead Data Analytics
Principal Data Analyst – AI, ML and Big Data
Principal Data Scientist
Senior Manager Data Scientist
Software Engineer Data Scientist
The industries listed below hire data scientists to extract vital information that helps accomplish groundbreaking progress.
Banking – for customer segregation, fraud detection, dealing with compliance requirements, offering customized services
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Finance – acquiring and storing data effectively for analyzing it in the future, integrating traditional and non-traditional data sets and creating predictive models
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Manufacturing – collecting data for source inspection and quality control to deliver better products efficiently
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IT Industries
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Technology
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Fraud and Risk Detection – utilizing data for profiling customers before sanctioning loans, understanding past expenditures and other variables to reduce risks
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Airlines – effectively predict flight timings and patterns, decide flight types and create exciting loyalty programs for customers
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Image Recognition – for security, automatic tag suggestion and generation of related search results
Speech Recognition – to convert speech to text accurately and communicate without typing commands or messages
Gaming – analyze a player’s moves and customize the game accordingly
Biotechnology – data compilation and analysis resulting in development of new medical devices and treatment methods
Energy – for installation and management of clean energy producing facilities
Telecommunications
Transportation – for development of cost-effective methods of transportation that reduce human effort