How to Hire a Data Scientist

Does your growing business need a data scientist? A data scientist will provide predictive analytics through designing and testing machine learning models.

Here are some tips to help you find great data scientist candidates and make the right hire for your business.

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Data scientists searching for jobs on Indeed*

166,339

Job seekers that clicked data scientist jobs

16,258

Resumes for job seekers with data scientist experience on Indeed

8,386

Data scientist jobs that received clicks

What is the cost of hiring data scientist?

  • Common salary in US: $119,725 yearly
  • Typical salaries range from $37,000$249,000 yearly
  • Find more information on Indeed Salary

*Indeed data (US) – April 2021

As of April 2021, data scientist jobs in the U.S. are moderately competitive compared to other job markets, with an average of 20 job seekers per data scientist job.

Why hire a data scientist?

Data scientists are a costly addition to your team. But if you’re focused on implementing machine learning and increasing your predictive power, a great data scientist can help you to:

• Predict consumer behavior as it relates to your product or service
• Build machine learning models that can automatically interact with your customers, e.g., recommendation systems, chatbots, etc.
• Greatly improve strategic decision-making by uncovering hidden relationships within the data

Deciding between a full-time vs freelance data scientist

Data scientists are available for hire in both full-time and freelance positions. A company might consider hiring a freelance data scientist for a short time to analyze their existing data and draw onetime conclusions. The business then uses that data to improve its current business practices and profits. 

Some businesses, however, may hire a full-time data scientist to constantly monitor their data. The full-time scientist provides the company with regular reports on the data, allowing them to continually use it to improve. Hiring a full-time employee can also be less expensive than a freelancer when working 40 hours a week. 

What are the types of data scientists?

There are a few types of data scientists who focus on different aspects of companies. These types include:

  • Quality analyst: Quality analysts typically work in the manufacturing industry. They use specific tools to measure the efficiency of assembly lines. Quality analysts improve the speed of work while maintaining product quality and meeting performance standards. 
  • Business analytic practitionersThese data scientists examine businesses’ procedures, data and employees to improve their investment returns. 
  • Actuarial scientists: Actuarial scientists usually work in financial institutions, such as banks and insurance companies. They use mathematical algorithms to predict future profits and losses from investments. 
  • Software programming analysts: Software programming analysts work to improve programs used by businesses to reduce computing time. 
  • Spatial data scientists: This type of data scientists uses spatial data to predict where and why specific things happen. They can also use this data to find correlations between events. 

Where to find data scientists

To find the right data scientist for your business, consider trying out a few different recruiting strategies:

  • Maintain relationships with local colleges and universities. By communicating with colleges in the area, you may be able to find leads on promising recent graduates in the data science field. 
  • Search online for established data scientists. There could be data scientists advertising themselves online. Make contact with these candidates to gauge their level of interest in the job and set up interviews. 
  • Network. Ask other businesses in the area for information regarding data scientists they’ve hired in the past. Reach out to these candidates to set up meetings. 
  • Post your job online. Try posting your data scientist job on Indeed to find and attract quality data scientist candidates.

What are the types of data scientists?

There are a few types of data scientists who focus on different aspects of companies. These types include:

  • Quality analyst: Quality analysts typically work in the manufacturing industry. They use specific tools to measure the efficiency of assembly lines. Quality analysts improve the speed of work while maintaining product quality and meeting performance standards. 
  • Business analytic practitionersThese data scientists examine businesses’ procedures, data and employees to improve their investment returns. 
  • Actuarial scientists: Actuarial scientists usually work in financial institutions, such as banks and insurance companies. They use mathematical algorithms to predict future profits and losses from investments. 
  • Software programming analysts: Software programming analysts work to improve programs used by businesses to reduce computing time. 
  • Spatial data scientists: This type of data scientists uses spatial data to predict where and why specific things happen. They can also use this data to find correlations between events. 

Writing a data scientist job description

A thoughtful description will attract highly qualified data scientist candidates. A complete data scientist job description includes a high-level summary of the role, a detailed list of duties and responsibilities and the required and preferred skills for the position.

When writing your data scientist job description, consider including some or all of the following keywords to improve the visibility of your job posting. These are the most popular search terms leading to clicks on data scientist jobs, according to Indeed data:

  • Data scientist
  • Data science
  • Machine learning 
  • Data analyst
  • Statistics
  • Mathematics
  • Data
  • Python
  • Data science intern
  • Math

Interviewing data scientist candidates

Strong candidates for data scientist positions will be confident answering questions regarding:

• Applied use cases for SQL, R, Python or the preferred programmatic method for collecting and cleaning data, then building a predictive model
• Machine learning concepts, such as unsupervised, supervised, semi-supervised, reinforcement learning and model optimization and tuning
• Advanced statistical methods

Need help coming up with interview questions? See our list of data scientist interview questions for examples (with sample answers).

FAQs about how to hire a data scientist

When should I hire a data scientist?

You should hire a data scientist when your business is ready to start focusing on growth and improvement. However, your business needs to be in a position where it has enough data to be analyzed. 

How do I choose between two quality data scientist candidates?

There are a few factors you could use to choose which candidate to hire. You can go with the candidate who has more experience with online technology or the one who fits in better with the team and has good communication skills. 

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