What to Expect in Data Science 2021 and Data Science Salaries 2020

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It’s an exciting time to be working in the world of Data Science.  Here is what to expect in data science 2021 and how your data science salary has been impacted.

Data Science Salaries 2020

This information may ring a few bells as we have not seen much movement in data science salaries since 2019. They have held very steady over the past year during the pandemic. Glassdoor.com reported on December 19, 2019 that from the 6606 salaries submitted anonymously by data scientists, the average base pay was $120K with additional cash compensation of, on average, $11,742. ZipRecruiter reported a slightly lower national average of $118K, but they also report that they see salaries ranging from $184K to $355K with the majority between $92K and $137K.

This majority range of data science salaries, between $92K and $137K, is more in line with what Nancy Darian and Paul Chatlos, Smith Hanley Data Science Recruiters, are seeing in their recruiting efforts. Paul says, “Data Scientists with one year of good, in depth experience can expect to earn a salary of 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 reported the average salary by state in those top ten states with the highest volume of data science job. Some of these variations reflect cost of living differences and some are driven by higher demand but all are impacting data science salary expectations for 2021

  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 $112,05
  8. Illinois $106,135
  9. Maryland $117,345
  10. Pennsylvania $103,995

What to Expect in Data Science 2021 for IoT

Statista estimates that in 2021 we will have nearly 36 billion IoT devices installed worldwide, a significant uptick from 2020. Research firm IDC reports that worldwide spending on Internet of Things (IoT) declined significantly in 2020 due to the economic effects of the pandemic, but that growth in spending will rebound in 2021 and beyond at a rate of over 11% year over year. Healthcare, insurance and education will represent the largest growth in IoT spending while industries such as hospitality and entertainment will grow more slowly.

What are some of the ways that IoT will affect our daily lives in 2021 according to Forrester?

  1. The worldwide pandemic has normalized new methods of patient care. Digital health devices will soar, as lifesaving sensors will help predict patient health conditions prior to physician consultations.
  2. Office buildings will use connected applications to improve worker safety and energy efficiency. Home devices will also provide protection and energy savings. Data from sensor-based motion, lighting, heating, and cooling will allow remote monitoring.
  3. In manufacturing, remote monitoring of machines, data and processes will continue to reduce costly downtime and employee travel.
  4. Consumer brands will continue to use location data to deliver personalized products and services to delight customers. The trend toward home delivery of goods will continue in the post-pandemic world.

What to Expect in Data Science 2021 for Artificial Intelligence (AI)

AI is one of the fastest moving and least predictable applications in the data science world. Here are some of the hot issues in 2020 that will continue in 2021.

  1. According to Rick Whiting of CRN, developers of cybersecurity systems will continue to update their technology to thwart threats from malware and ransomware attacks. In addition, “AI-powered cybersecurity tools also can collect data from a company’s own transactional systems, communications networks, digital activity and websites, as well as from external public sources, and utilize AI algorithms to recognize patterns and identify threatening activity.”
  2. Cade Metz of the NY Times summarizes an ethical concern with the rising use of AI enabled technologies in our homes. “Speech recognition systems from five of the world’s biggest tech companies — Amazon, Apple, Google, IBM and Microsoft — make far fewer errors with users who are white than with users who are black, according to a study published Monday in the journal Proceedings of the National Academy of Sciences. One of the key outcomes of the study was the quantification of bias in speech recognition. On average, these systems misidentified words spoken by whites 19% of the time vs 35% of the time for blacks. We see a big opportunity in 2021 to improve speech recognition systems to take into account race, gender, regional accents and other variables that distinguish voices.
  3. Advancements in the use of AI in computer-generated graphics will continue its exponential growth. This will lead to the proliferation of more and more deepfakes. The use of neural generation methods like deepfakes will create more realistic manipulations of text, photos, videos, audio and other multimedia that will be undetectable to humans.
  4. Autonomous vehicles, built with AI technology, will continue to grow in 2021. Automotive companies will accelerate research and development, making smart cars, and even flying cars a reality by 2025.
  5. According to Linchpin, the development of precision medicine will continue in 2021. Drug therapies will be produced based on individual patient diagnoses.
  6. Edge computing will take precedence over cloud computing. Instead of sending all the data to the cloud, the data will be transferred first to a local device located closer to the IoT device or at the “edge” of the network. The local source will sort, filter and calculate the data and then only part of the data will be 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 Data Science 2021 for Machine Learning

According to Linchpin, machine learning applications will continue to replace jobs in 2021 in virtually all industries. Below are some examples of how the growth of ML will continue unabated.

  1. Machine learning technologies will replace between 70-90% of basic customer service requests. Chatbots for example will save companies $8B over the next several years. Continued automation will result in a significant number of jobs in all industries disappearing next year. That trajectory is expected to continue for the foreseeable future.
  2. Machine learning will power autonomous systems in the military and will be able to determine with a high degree of accuracy whether an approaching vehicle is friendly or belligerent.
  3. Computer vision (powered by ML) will identify objects, affecting home security, driving, and healthcare.
  4. Machine learning algorithms will be coded in a more understandable way, improving human understanding of how AI works.
  5. Recommendation systems, used by retailers and streaming services for example, will continue to move from text to voice based command systems.

What to Expect in Data Science 2021 and Beyond for Remote Work

Due to the pandemic, we are seeing many positions that will allow new hires to start 100% remote. However, we are still seeing that most companies expect the person to eventually return to office environments once it is safe to do so. Nancy Darian adds, “We would say that one of the silver linings of the health crisis, is that companies have seen what employees can produce in a work-from-home environment. We foresee many organizations being open to 2-3 days a week from home in the future, but still having 2-3 days in the office. We think this hybrid model will be very popular once the pandemic is over.”

Interested in hiring a data scientist in 2021? Want to talk more about data science salaries for 2021, or your job growth plans? Reach out to Smith Hanley Associates Data Science and Analytics recruiters today.

Nancy Darian, ndarian@smithhanley.com
Paul Chatlos, pchatlos@smithhanley.com

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