The demand for data scientists has grown in recent years but at the same time it’s become more competitive to get a data scientist job. If you’re currently looking for a data scientist job and haven’t gotten any interviews or made it to the final round but still weren’t hired, what are your options? You can continue applying and hope you’ll eventually find a job, or consider a change in your job search strategy. Today I’d like to discuss alternatives to explore if you’re finding it difficult to get a data scientist job.
Not all data scientist jobs are equal
Positions with data scientist titles may not require building machine learning models to be the main responsibility. Look for data scientist jobs that are mostly data analyst responsibilities such as evaluating A/B tests and building dashboards with some modeling required. Since machine learning is just one responsibility, the technical interviews should be less complex if you’ve found it hard to pass more technical data scientist interviews. You’ll still be able to build models but part of your time will be working on data analyst tasks.
Apply to data analyst jobs
You’re probably wondering why you should apply to data analyst jobs when you’ve worked hard to become data scientist. Besides technical skills the top soft skills for a data scientist is communication skills and business acumen. Becoming a data analyst can help you build these soft skills if that’s the reason for your lack of success getting a data scientist job. Data analyst tasks have shorter turnaround time and will allow you to work on a wider variety of business problems to develop your business acumen compared to modeling projects which can take weeks or months to build and productionize. Being a data analyst requires you to learn how to communicate well to explain analysis results to stakeholders.
Taking a data analyst job doesn’t mean you can’t build models. Companies with data analysts and no Data Science team will give you the freedom to build models if it aligns with the needs of the business. As a data analyst I used machine learning models when it was the right solution for the business problem. Becoming a data analyst in a niche you’re interested in will help you understand the business. This will make you a stronger data scientist candidate in the future when you apply to similar businesses because you’ll already have the domain experience and require less training.
Additional options
Below are other options related to data science you can explore.
- If you’ve trained to be a data scientist then chances are your coding skills may be good enough to become a data engineer. This can be an option if you like Programming.
- If you’re interested in finance, look into quantitative analyst jobs. The work of quantitative analysts and data scientists overlaps and this may be of interest to you.
- Perhaps you like teaching others about data science. Consider creating your own courses on teaching platforms such as Udemy. Income from online courses will vary but there’s potential for instructors to make over $1M on Udemy. The courses can become part of your portfolio to showcase your knowledge to potential employers when you apply to data science jobs going forward.
- Freelance data scientists can charge upwards of $100 per hour and while it can be hard to get those initial jobs there’s potential to develop relationships with clients that can lead to long-term work.
- Lack of experience may be why you can’t get a data scientist job. Consider entering Kaggle competitions to showcase your data science skills and possibly win some money in the process with prizes up to $100,000.
As a data scientist you may think you should only apply to jobs that require building models but now you know there are other possibilities. The options I mentioned may not be ideal but the alternative could be staying in your current job which may be at risk because of budget cuts or not finding one if you lack experience. Regardless of the path you choose, I hope your job search ends sooner rather than later.
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