Hop Into the Data Scientist Bandwagon

Date: 23-Aug-2019
Location: Global

Key Takeaways:

• Found at the cross section of business and information technology, a data scientist is a professional with the capabilities to gather large amounts of data to analyze and synthesize the information into actionable plans for companies and other organizations. Data scientists are analytical data experts who utilize their skills in both technology and social science to find trends and manage the data around them. With the growth of big data integration in business, they have evolved at the forefront of the data revolution.
• On any given day, a data scientist is a mathematician, a statistician, a computer programmer and an analyst equipped with a diverse and wide-ranging skill set, balancing knowledge in different computer programming languages with advanced experience in data mining and visualization.
• Every company will have a different take on data science job tasks. Some treat their scientists as data analysts or combine their duties with data engineers; others need top-level analytics experts skilled in intense machine learning and data visualizations.
• Average Data Scientist Salary: USD $117,345 per year.
• Typical skills of data scientist:
  • Programming Languages: Python, R, SAS
  • Machine Learning Tools
  • Data Visualization and Reporting
  • Risk Analysis
  • Statistics and Math
  • Effective Communication
  • Software Engineering Skills
  • Data Mining, Cleaning and Munging
  • Big Data Platforms
  • Cloud Tools
• Data scientists don’t need to just understand programming languages, management of databases and how to transpose data into visualizations – they should be naturally curious about their surrounding world, but through an analytical lens. Possessing personality traits that resemble quality assurance departments, data scientists may be meticulous as they review large amounts of data and seek out patterns and answers. They are also creative in making new algorithms to crawl data or devising organized database warehouses.
• Some data scientists get their start working as low-level data analysts, extracting structured data from MySQL databases or CRM systems, developing basic visualizations or analyzing A/B test results.

William Iven


 Spokeperson:

• Josh Wills on Quora, said, a data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician.
• Lisa Qian, Data Scientist at Airbnb, said, a data scientist is involved in every step of a product’s life cycle. Every product team at Airbnb has engineers, designers, product managers, and one or more data scientists - data scientist uses data to identify areas that we should invest in and come up with concrete product ideas to solve these problems.
  • At Airbnb, we all use Hive (which is similar to SQL) to query data and build derived tables and use R to do analysis and build models - A lot of data scientists use Python instead of R - There have also been recent efforts to use Spark to build large-scale machine learning models.
  • Successful data scientists have a strong technical background, but the best data scientists also have great intuition about data.

Offerings:

• Data scientist certifications
  • Certified Analytics Professional (CAP)
  • EMC Proven Professional Data Scientist (EMCDS)
  • SAS Certified Predictive Modeler using SAS Enterprise Miner 14
• Post-graduate learning
• Professional Organizations for Data Scientists
  • Data Science Association
  • International Institute for Analytics (IIA)
  • International Machine Learning Society (IMLS)
  • Institute for Operations Research and the Management Sciences (INFORMS)
  • Association for Computing Machinery’s Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD)

Editor's comments:

• I think a data scientist is a think-tanker who derives decision making conclusions based on data and domain knowledge such as statistic, economics etc.
• Think of a data scientist as an internal consultant who performs similar feats as the McKenzie consultant, helping companies to derive decision making conclusions based on data (of both private owned and public domain.)
• A good data scientist must have a good of mix technical and domain knowledge skills and must be always willing to learn new technical skillsets
• Data scientists are racing time to compete with the rise of general A.I
• Therefore, the consulting industry gave birth to the data science field which in turn contributes to the rise of general A.I phenomenon.