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So you think you are a Data Scientist?

data scientistMany are writing articles about the skills required to be a data scientist. I disagree with 97.3% of them. Before you can be a data scientist, you must qualify to be a scientist. A degree in management does not qualify you to be a Chemical Scientist or Mathematical Scientist, nor does it qualify you to be a Data Scientist. However, there is nothing derogatory about being a data analyst, data processor, data architect, database administrator, and so on, but doing these jobs do not make you a data scientist. Neither does a few courses from Coursera.

Scientists perform research toward a more comprehensive understanding of nature, including physical, mathematical and social realms. Scientists are also distinct from engineers, those who design, build and maintain devices for particular situations. When science is done with a goal toward practical utility, it is called applied science. An applied scientist may not be designing something in particular, but rather is conducting research with the aim of developing new technologies and practical methods.

The following are requirements from a GSA Schedule. Many who call themselves Data Scientists are not qualified to be an assistant.

Assistant Scientist I/II

  • BS in engineering or equivalent
  • One to three years research experience or equivalent course/project work
  • Strong foundation in object-oriented analysis and design
  • Knowledge of and experience with a variety of software languages and platforms
  • Demonstrated research skills
  • Demonstrated ability to understand appropriate algorithms and concepts
  • Demonstrated ability to write clear, grammatically-correct documents
  • Demonstrated ability to effectively communicate and work with other members of project team
  • Strong analytical skills
  • Strong fit with Company goals and values (work ethic, attitude, interest in work)

Scientist I/II

  • MS (or BS plus three years of experience) in engineering or equivalent
  • Two to five years research experience or equivalent course/project work
  • Demonstrated object-oriented analysis and design skills
  • Knowledge of and experience with a variety of software languages and platforms
  • Proven research skills
  • Proven ability to understand appropriate algorithms and concepts
  • Demonstrated ability to employ a hierarchical writing process to generate clear, grammatically correct documents
  • Demonstrated ability to provide technical guidance to interns and other more junior team members
  • Strong analytical skills
  • Strong fit with Company goals and values (work ethic, attitude, interest in work)

Senior Scientist I/II

  • PhD (or MS plus four years of experience) in engineering or equivalent
  • Three to six years research experience or equivalent course/project work
  • Strong object-oriented analysis and design skills
  • Knowledge of and experience with a variety of software languages and platforms
  • Strong research skills proven by publication record or equivalent references from the research community
  • In-depth experience with appropriate technologies
  • Strong ability to employ a hierarchical writing process to generate clear, grammatically-correct documents
  • Two years of experience leading teams
  • Demonstrated program management skills
  • Strong analytical skills
  • Strong fit with Company goals and values (work ethic, attitude, interest in work)

Principal Scientist I/II

  • PhD (or MS plus five-years of experience) in engineering or equivalent Four plus years research experience or equivalent course/project work Strong object-oriented analysis and design skills
  • Knowledge of and experience with a variety of software languages and platforms
  • Superior research skills proven by extensive publication record or equivalent references from the research community
  • Expert knowledge of appropriate technologies
  • Demonstrated ability to write winning proposals
  • Three years of experience managing teams
  • Strong analytical skills
  • Strong fit with Company goals and values (work ethic, attitude, interest in work)

No wonder companies who are hiring data scientist are being disappointed in their performance and contribution. Too many people are watering-down the requirements.


Jeffrey Strickland

Authored by:
Jeffrey Strickland, Ph.D.

Jeffrey Strickland, Ph.D., is the Author of Predictive Analytics Using R and a Senior Analytics Scientist with Clarity Solution Group. He has performed predictive modeling, simulation and analysis for the Department of Defense, NASA, the Missile Defense Agency, and the Financial and Insurance Industries for over 20 years. Jeff is a Certified Modeling and Simulation professional (CMSP) and an Associate Systems Engineering Professional (ASEP). He has published nearly 200 blogs on LinkedIn, is also a frequently invited guest speaker and the author of 20 books including:

  • Operations Research using Open-Source Tools
  • Discrete Event simulation using ExtendSim
  • Crime Analysis and Mapping
  • Missile Flight Simulation
  • Mathematical Modeling of Warfare and Combat Phenomenon
  • Predictive Modeling and Analytics
  • Using Math to Defeat the Enemy
  • Verification and Validation for Modeling and Simulation
  • Simulation Conceptual Modeling
  • System Engineering Process and Practices

Connect with Jeffrey Strickland
Contact Jeffrey Strickland


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4 replies »

  1. I totally agree but I think a big part of that wrong usage of the “data scientist” term, comes from a misunderstanding (or not a clear definition) of “data science” in Itself. We can read everywhere about data science and I think this term is too generic. Its pretty much the same thing with music, it s broad there are instrumentalists of all kind, compositors, orchestrators, producers, arrangers (…) and also a lot of non professional people who just play music at home. And the problem is the same. who are the musicians? everybody that play music? professionals musicians with a lot of experience?, composers that actually create music? Is Paul McCartney a musician when he plays the songs that he wrote and just a bassist when he used to play songs by John Lennon?
    The parallel with data science is quite obvious. However if that domain continu to grow as fast as it does, people won t be able to do all by themselves . The same thing happened with video games, they used to be the creations of one guy and are now run by large teams and millions dollars budget (for some of them).
    So maybe we won t even see any phd in data science and skip directly to the step of enterprises recruiting phd in different domain to work on big “data science” project…time will tell

    Liked by 1 person

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