5 Tips for Negotiating Data Science Salaries

Since Data Science is new, salary negotiation is a tricky affair in this field. Not much is available on the salary offered in data science on public domain. So benchmarking is not always possible while negotiating the salary.

There are some general negotiation techniques that are applicable to all jobs. However, you must know some specifics to data science. This article is about what specific things to consider while negotiating salary in data science.

Here are the tips you should keep in mind while negotiating your salary

  1. Experienced people have higher bargaining power:  Since data science is a new, not many have long experience in this field. Hence there is a shortage of experienced professionals. If you have more 5 years of experience in data science, you have good bargaining power.
  2. Not all Sectors pay equally: All sectors employ data scientists. But some employ more than the others. For example, banking sector employs a large number of data scientists, as it produces massive amount of data and data based decision making is mandated by banking regulation. Moreover, banks normally hire those that already have banking experience. So you have higher bargaining power in banking/financial sector. Technology and Ecommerce companies pay high salaries, compared to say tradditional manufacturing companies.
  3. Some skills are hard to find in the job market: If you are a data scientist with strong experience in computer vision, NLP, deep learning (so called high end Machine Learning fields) then you can command higher salary. If you have experience in some proprietary software (such as SAP/SAS/Matlab) then also you can command higher salary.
  4. Secondary Skills play a big role: If you are a data scientist with prior software development experience, you can ask for higher salary. It is difficult to find data scientists that can develop software from scratch. If you are data scientist with marketing or sales experience, you will be highly valued in many places (such as retail/ecommerce). So if you have good secondary skills, ask for more money.
  5. Higher Education(M.Sc./PhD) level matters (though not in all fields): In many sectors, data scientists need to have a higher education at least at the level of a master degree. For example, in banking sector one has to be have a master/PhD degree to work in the regulatory modelling area. This added requirement makes it harder for banks to hire data scientists. Hence they pay higher salary. Consulting companies value higher education (and certifications) a lot, so that they can impress thier clients. So if you have PhD or any other graduate degree from top universities, you will be in great demand among consulting companies.

Some General Tips:

  1. Do your research. Learn the average salary for your experience level from glassdoor and other sources online. You may talk to your friends and colleagues that is not an issue.
  2. Talk to some HR folks in this field. They normally have good overview of the current market trend in the job market
  3. Do not quote your expectation first. Let your potential employer quote it first.
  4. Your currently salary does not matter for your future salaries (especially if your current salary is not very high)

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