*by Robert A. Muenchen*

This article describes the technical details of how to search for jobs in the field of data science. The results of the searches are displayed and discussed in The Popularity of Data Science Software. The protocols were implemented 2/27/2017 and they are significantly different from the previous set posted on 2/20/2014.

**Data Science Terms
**

Some software used for data science is also used by a wide range of other tasks. Let’s consider a few examples. General purpose languages, such as C, Java, or Python are used heavily for some data science tasks, but if you do a job search on just their names, the great majority of jobs found will not be for data science. Other software such as Cognos, SAS, and Tableau are very popular for simple report writing as well as for data science jobs. Therefore simple searches will find a blend of both types of jobs. Finally, some software, such as Apache Spark, SPSS, or Stata are very specific to data science. With such a mix of software, the challenge is to use search terms that will yield values that are comparable across all types of software.

To compile a list of search terms that are specific to data science jobs, I started out searching for jobs that required software that is used specifically for data science. I then looked for terms that often appeared in those job descriptions. Next, I searched for jobs that featured only those terms, one at a time. Some, such as “analytics” resulted in searches that were not well focused; jobs that had nothing to do with data science would appear. Others, such as “econometrics”, did indeed focus on data science jobs, but only in the field of economics. As I worked my way through these searches, I found more search terms to test. The results are shown in Table 1.

Search Terms |
Jobs Found |

Analytics (not well focused) | 123,895 |

Survey (not well focused) | 72,323 |

Statistics (not well focused) | 66,201 |

Statistical (not well focused) | 55,998 |

Big Data | 20,646 |

Analyze data (not well focused) | 20,068 |

Business intelligence (too much reporting) | 19,709 |

Data analytics | 15,774 |

Machine learning | 12,499 |

Statistical analysis | 11,397 |

Data mining | 9,757 |

Data Science | 6,873 |

Quantitative analysis | 4,095 |

Business analytics * | 4,043 |

Research associate (too vague) | 3,794 |

Advanced Analytics | 3,479 |

Data Scientist | 3,272 |

Statistical software | 2,835 |

Predictive analytics | 2,411 |

Artificial intelligence | 2,404 |

Predictive modeling | 2,264 |

Statistical modeling | 2,040 |

Econometrics (too focused) | 1,860 |

Quantitative research | 1,837 |

Research analyst | 1,756 |

Statistical tools | 1,414 |

Statistician | 904 |

Statistical packages | 784 |

Survey research | 440 |

Quantitative modeling | 352 |

Statistical research | 208 |

Statistical computing | 153 |

Research computing | 133 |

Statistical analyst | 125 |

Data miner | 34 |

Table 1. Terms used in data science job descriptions

Ideally, one could include all the focused terms in a search, but Indeed.com’s search feature limits the size of the search string. To determine the maximum string size, I put in the longest software string and then added in the data science terms. The data science terms then truncated to show the limit. Table 2 shows the resulting set of search terms that I used to append to each software title. For example, when searching for Java, I would enter: Java and (“big data” or “data analytics” or …”statistician”).

and ("big data" or "data analytics" or "machine learning" or "statistical analysis" or "data mining" or "data science" or "quantitative analysis" or "business analytics" or "advanced analytics" or "data scientist" or "statistical software" or "predictive analytics" or "artificial intelligence" or "predictive modeling" or "statistical modeling" or "quantitative research" or "research analyst" or "statistical tools" or "statistician")

Table 2. The **data science terms** and logic that are appended to every job search.

**Additional Challenges**

Some software offered additional challenges. Those with letter names, C and R, were found using spaces before and after their names, such as (” R ” or ” R,”) . This isn’t a perfect solution since it would count an advertisement for a data scientist skilled in SAS at the “Toys R Us” company as a job for an someone with R skills. Conversely, the search for an R programmer at the SAS Shoe company would also be counted as one for a SAS programmer. Many of these searches have flaws like that, but the size of the search limits the accuracy. However, if you look through the resulting job advertisements, you’ll see that errors with this search approach are rare.

When advertisements list the C language, it’s most often in the form of “C, C++, or C#” so no attempt was made to differentiate those variants. However Objective C was usually advertised for iPad or iPhone application development, so it was excluded.

Microsoft presented another challenge. Just its name combined with the data science terms yielded results that were heavily biased by the inclusion of general-purpose tools such as Microsoft SQL Server. Focusing the search with (“Azure Machine” or “Azure Stream” or “Microsoft R” or “Cortana Intelligence” or “Microsoft Cognitive” or CNTK) used up so much space that two of the data science terms had to be dropped: “statistical tools” and “statistician”.

Another challenging search was for Domino Data Labs’ Data Science Platform. The search (Domino and “Data Science Platform”) found no jobs, not even for those from the company itself! Just the term “Domino” along with the data science terms found mostly job descriptions that mentioned Lotus Domino. For the 2017 search, I simply culled the small number of results down by hand.

Similarly, the search for Alpine and the data science terms yielded hits that were mostly irrelevant, so I culled them manually.

**The Search Terms**

Table 3 shows the search terms used for each software. See Table 1 for the data science terms that were appended to every search except Microsoft, whose complete search is shown below.

Alteryx and data sci terms Amazon: I'm leaving Amazon and Microsoft very loosely defined: (Amazon or AWS) and data sci terms Becuase when I focus it using the following, it misses too many: ("Amazon Machine Learning" or "AWS Certified Machine Learning") and data sci terms Anaconda and data sci terms (drop Flink next year; not general enough) Apache Hadoop: Hadoop and data sci terms Apache Mahout: Mahout and data sci terms Apache Flink: Flink and data sci terms Apache MXNet: MXnet and data sci terms Apache Pig: Pig and data sci terms Apache Spark: Spark and data sci terms BigML and data sci terms "BlueSky Statistics" and data sci terms BMDP and data sci terms ("C programmer" or "C programming" or "C developer" or "C++" or "C#") and !("objective c") and data sci terms Caffe and data sci terms "Civis Analytics" and data sci terms Cognos and data sci terms Databricks and data sci terms Dataiku and data sci terms DataRobot and data sci terms Deducer plus data sci terms Domino Data Labs: "domino data" and data sci terms [Beware of just "domino" as it gets pizza data sci jobs!] FICO [avoid this one; too hard to focus away from credit scores] FORTRAN and data sci terms Google: Google and data sci terms I've greatly simplified this one along with Amazon and Microsoft as it's hard not to undercount otherwise. Compare to this old version: ("Google Cloud Machine Learning" or "Google Cloud AutoML" or "cloud Dataproc" or "Cloud Datalab") and ("big data" or "data analytics" or "machine learning" or "statistical analysis" or "data mining" or "data science" or "quantitative analysis" or "business analytics" or "advanced analytics" or "data scientist" or "statistical software" or "predictive analytics" or "artificial intelligence" or "predictive modeling" or "statistical modeling" or "quantiative research" or "research analyst") so it's missing: or "statistical tools" or "statistician" (graphPad and Prism) and data sci terms H2O: "H2O" and data sci terms Hadoop and data sci terms IBM SPSS: (SPSS and !"SPSS Modeler") and data sci terms IBM SPSS Modeler: "SPSS Modeler" and data sci terms IBM Watson: "IBM Watson" and data sci terms JASP and data sci terms jamovi and data sci terms Java and data sci terms JMP and data sci terms Julia and data sci terms Keras adn data sci terms KNIME and data sci terms Lavastorm and data sci terms Lasagne and data sci terms [check this carefully] Mathematica and data sci terms MATLAB and data sci terms (Megaputer or Polyanalyst) and data sci terms Minitab and data sci terms Microsoft: Azure and data sci terms MLlib and data sci terms NCSS and data sci terms OpenText and data sci terms ("OriginPro" or "OriginLab") and data sci terms [Just "origin" vastly overcounts.] Pentaho and data sci terms Python and data sci terms Pytorch and data sci terms R: (" R " or " R,") and data sci terms "R Commander" and data sci terms RapidMiner + data sci terms Rattle: (Rattle and !"Rattle off") and data sci terms RKWard and data sci terms ("SAP Predictive" or "SAP Automated" or "SAP Leonardo" or "SAP Hana") and data sci terms SAS: (SAS !"Enterprise Miner") and data sci terms SAS Enterprise Miner: "Enterprise Miner" and data sci terms Scala: "Scala" and data sci terms "Scikit Learn" and data sci terms "Splunk" and data sci terms SQL and data sci terms Stata and data sci terms Statgraphics and data sci terms Systat and data sci terms Tableau and data sci terms Tensorflow and data sci terms Theano and data sci terms Tibco: (tibco or spotfire or statistica) and data sci terms Vowpal Wabbit WEKA and data sci terms World Programming: "WPS Analytics" plus data sci terms [Test it this way]

Table 3. Search terms used for each software (see Table 1 for data science terms).

**Searching for Trends**

Indeed.com has a Job Trends tool that lets you see how jobs are changing across the last several years. You can enter one or more searches from one of the examples above to see the trends. Unfortunately, the search for trends must be much simpler than Indeed.com’s main job search.The best pair of queries I could get to compare R and SAS is:

R and ("big data" or "data analytics" or "machine learning" or "statistical analysis" or "data mining" or "data science") SAS and ("big data" or "data analytics" or "machine learning" or "statistical analysis" or "data mining" or "data science")

Now that you’ve got the details, check out the results here. I’m very interested in improving this methodology so if you have ideas, please comment below or send me email at muenchen.bob@gmail.com.

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A very good study indeed. By the way do you use the Advanced Job Search Option on indeed.com or on the ordinary search option .

Hi Soumya,

I used the standard search. My searches were so specific that I did not find the advanced search added any capabilities that I needed.

Cheers,

Bob

Very good study . By the way are you using the Advanced Job Search to get the numbers or the ordinary search option ?

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Thanks Bob – applied to several positions today using this precise methodology… Wonderful!

Hi Joe,

Since my goal was to measure the popularity or market share of analytics tools, it did not even occur to me that people would use this info to actually find jobs. Doh! I’m glad it helped!

Cheers,

Bob

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This is an extremely helpful post for people who are looking for jobs in the Data Science industry. Using advanced search is quite effective to find the posts you are looking for. Thank you for sharing this!

Hi ProQuotient,

I’m glad you’re finding the site useful!

Cheers,

Bob

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Indeed.com should have a classification for employers for “Data Science ” for all of the “data scientists ” from different industries. Therefore, job hunting would be much easier for potential data scientists. Thanks for the articles.

Hi Africa,

If you look at their “advanced search” you’ll see the fields they allow you to search on. I’m searching on all fields, and it’s very fast. They could create a classification system where you would choose a category, like “Science & Technology” and then choose a subcategory like “Data Scientist”, but it would be a big job for them to maintain as terminology changes.

Cheers,

Bob

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