Already have an account? Log in.
The job market for data scientists continues to grow, with demand consistently increasing. Job posts for data scientists increased by 75% between 2015 and 2018. As per 2023 data from the U.S. Bureau of Labor Statistics, data scientist is the fourth-fastest growing occupation in the U.S. Furthermore, the U.S. BLS expects data scientist employment to grow 36% between 2021 and 2031. According to projections by the U.S. BLS , 40,500 new data science jobs will be created by 2031.
This article provides a comprehensive guide on how to hire a data scientist, focusing on best practices, practical advice and industry insights.
Hiring a data scientist offers significant benefits to tech companies, as they can play an important role in improving business outcomes. Data scientists use their skills to:
Several tech and digital platforms have used data scientist skills to transform business performance. These include Chick-fil-A’s successful use of 3D cameras, data analytics and edge computing to build an IoT platform to keep its hot food fresh. Similarly, Netflix has used real-time viewer behavior analysis to increase subscriptions.
While hiring data scientists presents an expense, the benefits of this investment for tech companies are likely to be long-term. The median salary of a data scientist in the U.S. is approximately $108,020. Salaries can vary depending on the industry, skills and qualifications, experience, location and job responsibilities, but on average, data scientists can cost between $60,000 to over $200,000 a year.
Salaries are likely to increase with more experience. For example, the entry-level salary for a data scientist is around $87,000, but someone with five to nine years of experience can earn $113,000 annually. The average salary for a data science manager is approximately $126,506.
Hiring managers can use different avenues to find qualified and experienced data scientists. These include:
Data scientists are in high demand. Therefore, there’s significant competition among tech companies to hire top-tier talent in this field. When hiring data scientists, it’s important for hiring managers to attract the candidate by successfully conveying what their company has to offer. It’s essential to follow a step-by-step process when hiring data scientists. These steps include:
Here are some useful tips for hiring a data scientist:
The job requirements for data scientists have changed rapidly in recent years due to evolving technology. Some of the most important requirements, skills and qualifications include:
A job description should be able to attract top data scientists. An effective job description should ideally include:
It’s important to outline a hiring funnel for data scientists and include best practices for each stage, such as:
Here are some useful tips and strategies for interviewing data scientist candidates:
Specifically, it’s essential to assess the coding skills of data scientists. This can be achieved through:
After identifying the right candidate, it’s important to make an attractive offer to ensure you can acquire that talent. Hiring managers should ensure the offer includes the following:
Some common mistakes that tech companies make when recruiting data science talent are writing job descriptions that lack clarity, overemphasizing degrees, ignoring soft skills, overfocusing on technical skills, rushing the process and ignoring diversity and inclusion.
The most in-demand technical skills for data scientists in 2024 are SQL, R, and Python programming, statistical analysis, machine learning, data visualization, data wrangling, data transformation and cleaning, Big Data, database management, cloud computing, statistical software, NLP and Git.
Overall, data scientist can provide significant benefits to tech companies. Contact our team for guidance and support in screening, identifying and hiring the most qualified data scientists.
Dice Staff
