data science salary expectations

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Data Science and Analytics Recruiters, Nancy Darian and Paul Chatlos, give you their data science salary expectations going into 2020 and the hottest trends in the data science industry.

Data Science Salary Expectations

Glassdoor.com reports on December 19, 2019 that from the 6606 salaries submitted anonymously by data scientists the average base pay is $120K with additional cash compensation of, on average, $11,742. ZipRecruiter reports a slightly lower national average of $118K, but they also report that they see salaries ranging from $184K to $35.5K with the majority between $92K and $137K. This majority range is more in line with what Nancy and Paul are seeing in their recruiting efforts. Data Scientists with one year of good, in depth experience can have salary expectations around $100K. Once a data scientist has two or more years of experience, particularly with more advanced techniques like machine learning, their salary expectations can start to exceed $120K. Senior data scientists with on-going, hands-on skills, who can also manage other data scientists can look for pay above $140K, as can those data scientists with 4+ years of experience.

Springboard.com reports the average salary by state in those top ten states with the highest volume of data science jobs: 1. California $142,338, 2. Washington DC $105,975, 3. New York $115,815, 4. Virginia $98,216, 5. Washington $117,345, 6. Texas $101,208, 7. Massachusetts $112,059, 8. Illinois $106,135, 9. Maryland $117,345 and 10. Pennsylvania $103,995. Some of these variations reflect cost of living differences and some are driven by higher demand but all impacting data science salary expectations for 2020.

What to Expect in 2020 for IoT

Research firm IDC says there will be 41.6 billion Internet of Things (IoT) devices collecting and storing data in the next six years. Gartner says there will be 20 billion devices connected to the IoT by 2020. In 2020 that could mean 79.4 zettabytes of data to analyze. Where is this growth happening?

  1. Smart home devices will soar in popularity. Intelligent thermostats and smart lighting help conserve energy and reduce bills. Predictive maintenance information can be actively provided by IoT. Plumbing leaks, appliance failures and electrical problems can be addressed before they become major problems.
  2. The utilities industry is the largest user of IoT endpoints with nearly 1.2 billion per year. Smart meters in commercial and residential markets are driving this growth.
  3. Smart cities will become mainstream. Cities can unlock sustainable development, decrease traffic congestion and improve security through the use of IoT devices. Energy and resource management rely on a better understanding of consumption.
  4. Industrial and automotive sectors will be big drivers of IoT data growth. The complexity of sensors in automobiles and the value of machine sensors to improve quality in manufacturing will drive a 60% annual growth rate.
  5. Healthcare will see increased IoT adoption. Mobile health applications and virtual assistants to monitor and drive patient compliance will become more pervasive.
  6. Personalization of the retail experience through more efficient supply chain management as well as consumer services like discounts on regularly purchased products while you are still in the store and even maps directing you to purchases you have historically preferred will proliferate.

What to Expect in 2020 for Artificial Intelligence (AI)

AI is one of the fastest moving and least predictable applications. Here are some of the hot issues for this application in 2020.

  1. Ethics, explainability and trust will receive greater attention. “2019 saw the emergence of early principles for AI ethics and risk management and there have been early attempts at operationalizing these principles in toolkits and other research approaches,” says Karthik Ramakrishnan, head of advisory and AI enablement at Element AI. The European Community published a set of guidelines for developing ethical AI and Microsoft and Google have taken steps toward making their AI development conform to ethical norms.
  2. Advancements in the use of AI in computer-generated graphics will continue its exponential growth. Of course, this is also leading to the proliferation of more and more deepfakes. The use of neural generation methods like deepfakes will create even more realistic manipulations of text, photos, videos, audio and other multimedia that will be undetectable to humans.
  3. “We predict drug discovery will be vastly improved in 2020 as manual visual processes are automated because visual AI will be able to monitor and detect cellular drug interactions on a massive scale,” says Emrah Gultekin, CEO of Chooch. No longer will researchers have to hunch over their microscopes or sit in front of screens with clickers in their hands counting cells.
  4. Predictive text has been around for some time but the integration of AI will write your text before you do. Smart email predictive text is already being tested in GMail.
  5. Edge computing will take precedence over cloud computing. Instead of sending all the data to the cloud the data is first transferred to a local device located closer to the IoT device or at the “edge” of the network. The local source sorts, filters and calculates the data and then only part of the data is sent to the cloud reducing traffic to the network. This faster performance and reduced latency has significant positive implications within the manufacturing industry.

What to Expect in 2020 for Machine Learning

According to Statista the total funding allocated to machine learning in the first quarter of 2019 was $28.5 billion. Growth in the utilization of machine learning is expected to continue unabated.

  1. Cloud storage is more affordable and scalable. Data Lake storage is gaining traction as it allows unstructured data to be stored until it is ready for use. As storage becomes cheaper and easier more businesses will see the benefits of adopting machine learning.
  2. In conjunction with cloud computing the use of “digital data forgetting” uses machine learning to help identify unnecessary data that can be removed on command saving the time consuming effort of deciding which data to save and which to delete.
  3. In developed countries 20% of citizens will use virtual assistants for everyday tasks in 2020. The general movement to voice, Siri and Alexa, is creating individualized experiences and streamlining conversations. Machine learning accelerates the advancement of natural language processing by retraining models to be more accurate.
  4. Predictive analytics and machine learning when used in tandem lead to more powerful predictions. Rapid adoption of these applications will drive growth in multiple consumer industries.

Interested in hiring a data scientist in 2020?  Want to talk more about data science salary expectations for 2020, or your job growth plans?  Reach out to Smith Hanley Associates‘ Data Science and Analytics recruiters today.

Data Science and Analytics Executive Recruiter, Nancy Darian, [email protected]
Data Science and Analytics Executive Recruiter, Paul Chatlos, [email protected]


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