Data Science Skill Segmentation by Major Employers
As data science has matured into one of the most promising careers options in STEM, it is becoming increasingly important to understand the various aspects of and opportunities in this field. In order to do that we have gathered data from jobs posted by some of the most sought after employers in the US to develop a better understanding of how these companies use data science and machine learning in their operations. Some of the companies we sampled are:
Microsoft- Headquartered in Redmond, Washington Microsoft develops and sells software,c consumer electronics, computers and related services. Its best known software products are the Microsoft Windows and the Microsoft office suite. Microsoft is one of the largest companies in the world in terms of market cap (currently the largest) with a revenue of $143 Billion and an operating income of $53 Billion.
Amazon- It is the largest E-commerce company in the world headquartered in Redmond, Washington. With annual revenues at $280.5 Billion and an operating income of $14.5 Billion it is one of the most powerful companies in the world with a very strong presence in cloud computing, artificial intelligence and digital media as well.
Apple - The company behind the iphone and the ipad, Apple is undoubtedly one of the most well known tech companies in the world. This behemoth is headquartered in Cupertino, California with a very strong portfolio in consumer electronics, software, digital media,cloud computing etc. Apple’s 2019 revenue was $260.2 Billion and an operating income of $63.9 Billion.
Facebook - It is the largest social network in the world. Headquartered in Menlo Park, California. Facebook’s product base also includes Instagram, Watsapp and Oculus VR. The tech giant earned a revenue of $70.7 Billion in 2019 with an operating revenue of $23.9 Billion.
NVIDIA - This technology major develops graphics processing chips and system on a chip units for the electronics and automotive market. The company is headquartered in Santa Clara, California with an annual revenue of $11.7 Billion (2018) and an operating income of $3.8 Billion.
Alphabet - The parent of Google is based out of Mountain View, California and has an impressive portfolio including products in software, artificial intelligence and self driving cars etc. Alphabet earned a revenue of $161.8 Billion in 2019 with an operating income of $34.2 Billion.
Uber - The largest ride sharing network in the world first achieved its unicorn status only 6 years after its inception. The company is based out of San Francisco, California and earned revenues of $ 14.1 Billion in 2019.
The companies mentioned above are some of the most well known tech giants in the world and highly sought after employers for a lot of STEM professionals including data scientists and machine learning engineers. A lot these companies have made a significant contribution to this field like Facebook created Pytorch - one of the most popular deep learning frameworks in the world. Alphabet owns DeepMInd which is an AI research firm famous for AlphaGo (the AI based program that beat the human world champion in Go) and Nueral Turing Machines. With achievements like that in their kitty, these companies are undoubtedly a top choice for many data scientists.
Position Types Analyzed from Job Descriptions
Average Experience Based on Position Types and Employers Analyzed
A quick look into the job profiles we analyzed reveals that a significant portion of the job opportunities were in engineering teams (56.7%) which 18.1% of the positions were in research. 24.0% of the positions were in management. A very small number of leadership positions (directors and above) were also available. We delved a little deeper into the different position types and the employers we included into our analysis. We found that all the employers analyzed had similar experience requirements for engineering positions (between 5-6 years). As expected leadership positions had the highest requirements for experience. Out of the analyzed employers Facebook and NIVIDIA had the highest requirements for leadership positions at 15 years and 13.5 years. Management positions required an experience level between 6.5 to 7 years consistently between all employers. Scientists similarly had a tenure requirement between 3 - 5 years across all employers. One issue with the analyzed data was the high standard deviation in the tenure of scientists at Facebook.
Applications of Artificial Intelligence by Company
Academic Requirements by Employer Analyzed based on Job Descriptions
Looking more into our data on job descriptions we analyzed how artificial intelligence is being applied at different companies we looked into. We looked for applications like deep learning and big data analytics to get a better insight into how different companies use AI. Out of all the organizations analyzed we found the most extensive use of deep learning was done by NVIDIA. Over 88.2% of the job descriptions from the company had required specialized deep learning skills. The second largest user of DL skills was Facebook with 43.8% of the jobs requiring knowledge in this field. 41.8% of job postings from Apple required a knowledge of deep learning. Big data analytics on the other hand was most ubiquitously found in the job descriptions from Amazon (38.5%) followed by Microsoft at 32.7%. A similar analysis with educational qualifications was also undertaken to garner a better understanding of what levels of education were typically required by the different employers we analyzed. Job descriptions from NVIDIA and Apple had the highest percentages of master’s degree requirements. Particularly 88.2% of jobs from NVIDIA required a master’s degree. Following NVIDIA, 74.0% of the jobs at Apple required a master’s degree. In terms of doctoral degree requirements, job descriptions from Uber and Google were found to have the highest (64.7% and 50.0% respectively). Job descriptions from NVIDIA and Facebook also showed a strong requirement of PhD candidates at 38.2% and 37.0% respectively. Overall, it can be easily inferred from the data that advanced degrees were strongly required by most of the employers (some more than others), which means for candidates looking for DS/ML positions can definitely benefit from investing into a advanced degree.
Preference for Programming Languages by Company
We also looked into the type of programming languages used at the different companies we analyzed. The data suggests that in most of the organizations Python was the most ubiquitously used programming language. Particularly, Python was found in 72.2% and 70.6% of job descriptions from Google and Uber. Following these two Apple was at 60.6%. We also found that C and C++ were very popular in NVIDIA found in 50% and 64.7% of the job descriptions, surpassing Python. C and C++ were popular with the other companies we analyzed as well, however at relatively lower levels than NVIDIA ranging at ~30% for C and 40% for C++ on the average. Java was the most popular in Amazon, Uber and Apple with 53.4% (surpassing Python), 52.9% and 43.8% of the job descriptions mentioning the language. Java was highly mentioned (at relatively lower levels) by other companies as well making it one of the top 4 of the most popular ones. R Studio was found to be relatively popular at Microsoft with 33.6% of the job descriptions referencing it along with Uber with 29.4%. Out of all the companies analyzed we found that Ruby was used moderately at Amazon and Apple while Scala and Perl were also moderately used by almost all the companies (found in ~10% of the job descriptions). PHP was found almost exclusively at Facebook with in 16.4% of their job descriptions. Similarly, Kotlin was found in 11.8% of Uber’s job descriptions.
Applications of Deep Learning by Company
Deep Language Packages used by Company
Deep learning is an important sub field of artificial intelligence and a significant number of companies are using DL to solve crucial technological problems. We classified deep learning processes into five sub classes and analyzed job opportunities from various companies which applications of deep learning. We found that natural language processing was the most ubiquitously found application in all job descriptions. In particular we saw that 33.3% of Google job descriptions required NLP skills. Computer Vision followed with significant application at Facebook and NVIDIA. 27.4% and 26.5% of job descriptions from these companies listed CV as a skill. Image Processing was widely found in ob applications at NVIDIA (13.2%). We also analyzed which different deep learning tools were being employed at the various companies we analyzed. We found a strong preference towards Tensorflow and Pytorch among all employers. However, we saw a significantly higher mentions of these two packages in job descriptions at NVIDIA (largely attributed to the fact that most job descriptions had a deep learning at NVIDIA). We also found Amazon relatively partial to MXNet. We also found Keras was also used moderately across all the employers we analyzed.
Big Data Tools by Company
We also looked into different big data tools used by different companies using their job descriptions. We found extensive use of Hadoop particularly at Uber and Apple. Similarly we also found extensive use for Hive and Kafka as well. We also found that Amazon had a preference for Redshift and DynamoDB. We also found moderate use of Tableau and Cassandra.