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The Most Important Aspects of a Data Science

Often touted as one of the top jobs of the 21st century, a data scientist is an increasingly common requirement across firms of different sizes and from a variety of verticals. This comes from the fact that: 

  • Massive amounts of data are flowing into most companies
  • This data is looked at as potentially a great source of valuable strategic insights

In the course of a data science career, a data scientist handles a number of responsibilities. The key purpose is to support product, marketing, and leadership teams with insights gleaned through data analysis of large data sets. Some specific responsibilities are mentioned below: 

  • Extracting and analyzing data from company databases for insights on how to optimize their product development and business strategies
  • Creating custom data algorithms
  • Organizing and using predictive modeling to design better user experiences, generate revenues, and improve targeting and business outcomes
  • Developing tools to monitor and analyze the performance
  • Coordinating with different functional teams to implement models and monitor outcomes
  • Searching for new tools to increase the accuracy and effectiveness of data sources

To be able to complete these responsibilities, a candidate is expected to possess the following set of data scientist qualification and skills: 

  • Programming languages such as Python, R, or MySQL
  • Creating data architectures
  • Machine learning (ML) techniques and their advantages or drawbacks
  • Ability to work with Google Analytics, DigitalOcean, Facebook Insights, Redshift, or other Internet-based tools
  • A holder of a degree from a university or college, or a certified data scientist
  • Good communication skills
  • Strong problem-solving skills

For a better understanding, take a look at data scientist qualifications, along with roles and responsibilities, categorized as per the stage in the career. 

Entry-level data scientist 

This is typically someone who has recently acquired a degree and is either looking for a first job or has just joined work. For the employer, the focus is on imparting learning through special training programs, to start off their data science careers. Their actual tasks include data analysis as well as using ML for day-to-day work tasks, among others. The chief requirements in terms of qualifications and skills include:

  • A college degree in a related discipline
  • A supplementary online course or data science certification from a recognized provider
  • Motivation, passion, ability to work hard, and desire to learn

Salaries, though obviously lower than more experienced data scientists, are still quite impressive, with an estimated average of USD 68,999 per annum. 

Junior data scientist 

At this stage of a data science career, the person is expected to be able to work independently, without close supervision from peers or seniors. The person, by this time, has some work experience and more than a basic idea of what is to be done. Tasks include data mining, and creating data analysis frameworks and tracking their performance, among others. The chief requirements in terms of qualifications and skills include: 

  • A college degree in a related discipline
  • More focus on execution than learning
  • The ability to make decisions under pressure
  • Motivation and passion for data science, along with a desire and willingness to work hard

Annual salaries range from a low of USD 62,000 to a high of USD 120,000, with an average estimated at USD 86,672. 

Senior data scientist

Considered an expert in the field, a senior data scientist has typically worked with all of the different tools required in the field. The person would have a thorough knowledge of not only the particular specialty but also other relevant aspects (for instance, a strong command of data analysis). Top skills at this level include: 

  • Knowledge of data visualization tools
  • Using query languages for data science
  • Strong statistical skills

Salaries per annum range from USD 99,000 to USD 181,000, with an average of US 134,222. 

At this level, it helps to be a certified data scientist, and a great choice of certification is the Senior Data Scientist (SDSTM) from the Data Science Council of America (DASCA). Considered the most powerful credential in the world for accomplished data scientists, this is targeted at professionals with at least 10 years of experience in big data analytics or big data engineering. 

For someone looking at a career in data science, the rewards are immense, but there has to be a determination to learn and progress on the career path.

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Tags: career, certified, data, qualifications, science, scientist

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