How to Hire Data Scientist | A Complete Guide

Nowadays many businesses are flooded with data and find it difficult to interpret it all. It’s getting even more difficult for companies and Recruiters to hire the right data scientists to help interpret this data. Due to this situation last year, the demand for data scientists has increased by 28%globally.

Apart from this many companies are unaware of which hiring practice is suitable to hire a data scientist, how to evaluate them, where to find them, etc.

To address this problem, we have created a detailed guide on everything a recruiter should know before hiring data scientists.

Let’s take a look and start with the core question. 

What is Data Science?

Data Science is the study to obtain data in the form of important business insights. To analyze this data in a large volume, data science is a multidisciplinary method that combines ideas and methods from computer engineering, artificial intelligence, statistics, and mathematics. And of course, the people who learn this skill are data scientists. 

• Trend forecasting: This helps in foreseeing future changes in the market, and data scientist analysis present and historic data for near to accurate forecasts.
• Making Informed Decisions: After extracting data businesses can make informed decisions that are backed up with numbers, facts, and strategies.
• Finding development Opportunities: Data scientists use this data to find what potential developments are possible and what areas businesses need to be worked on to get better results.
• Risk management: Data scientists also assist businesses in foreseeing the risks and damages by spotting trends and possible hurdles.
• Improving Customer Experience: Data science is a personalized experience for each business and can give unique solutions or insights as per the business. This also helps businesses in giving their users a more customized experience.
• Operational Efficiency: Data Scientists help in saving time and money. The suggested improvements and suggestions can save the business from many mishaps in the future.

Data Analyst vs. Data Scientist: What’s the Difference?

Data Scientist

Data Scientists combine advanced analytics, machine learning, and data modeling to predict future trends and get useful insights. They normally hold degrees in computer science or statistics and their aim is to provide strategic decision-making facts and innovate by understanding complex datasets while developing predictive models.

Skills Required

• Good at programming (especially in Python and R) and using special tools to analyze data.
• Understand complex math and statistics.
• Can organize, show, and use data to make predictions.

Tools and Technologies

• Programming languages: Python, R, SQL.
• Big data tools: Hadoop, Spark.
• Tools for making predictions: scikit-learn, TensorFlow.
• Programs to create graphs and charts.

Data Analyst

Data Analysts look at data to help companies understand what’s happening now. They usually have a degree in subjects like math or economics and focus on finding patterns, making charts, and explaining what the data means so companies can make smart decisions.

Skills Required

• Great at analyzing data with software and SQL.
• Can make and understand charts and graphs using special programs.
• Able to explain complex data in a simple way.

Tools and Technologies

• Databases: SQL, Excel.
• Statistical tools: R, SAS.
• Visualization tools: Tableau, Power BI.
• Basic coding skills for sorting and checking data.

5 Reasons Why Data Scientists Can Help In Business Growth

1. Improving Management’s Decision-Making Capabilities

   A data scientist measures, tracks, and records performance metrics and other information to help explain and illustrate the value of the institution’s data to support better decision-making processes throughout the entire company.

2. Directing actions based on trends

   After reviewing and analyzing the business’s data, a data scientist makes recommendations and recommends specific measures that would enhance the business’s operations, improve the experience of its users, and eventually boost profit.

3. Encouraging the Team to Adopt Best Practices

   A data scientist’s responsibility is to make sure that team members are informed about the company’s data. By showing them how to use the system effectively to extract insights and promote action, they set them up for success. After team members are aware of the potential of the product, they may concentrate on solving important business problems.

4. Identification of Opportunities

   Data scientists challenge the organization’s current processes and assumptions when working with its analytics system to create new techniques and analytical algorithms. It is their responsibility to continually boost the value that can be gained from the business.

5. Making Decisions Using Data-driven and Measurable Information

   The growth of data scientists has reduced the necessity for taking high-stakes risks by collecting and analyzing data from a variety of sources. Using already-existing data, data scientists create algorithms that recreate a range of possible actions. This allows an organization to determine what strategy will result in the best business outcomes.

What are the Skills Required to Become a Data Scientist?

Developing proficiency with data is an important set of skills for a Data scientist.

Other than that, everything from programming languages that help in understanding data to methods of statistical analysis, machine learning, and other fields are in demand. As data scientists are an important part of bridging the gap between complex data studies and practical business strategy, the fundamental skills needed by data scientists are listed in the following table:

What is the Cost of Hiring a Data Scientist?

When considering hiring a data scientist, it is important to understand the elements that determine the cost. The cost of hiring these experts can differ greatly. It is dependent upon their professional history, location, and the complex nature of the jobs they perform.

Source: capturly

How to Evaluate Data Scientist Candidates

Evaluating candidates’ technical and soft skills using techniques like coding tests to determine technical ability and data analysis projects to determine problem-solving skills will help you evaluate data scientist candidates more effectively.

How to Evaluate the Technical Skills of Data Scientists?

• Coding Assessment: To evaluate their ability in languages related to data science you can assign them custom challenges.
• Data Analysis Projects: Test them using practical data analysis assignments to understand howthey use their skills to address issues and how creative they are with solutions.
• Machine Learning Concepts: Evaluate their knowledge of machine learning concepts and talk about the methods and applications in their experience.

How to Evaluate Soft Skills Assessment of Data Scientists?

• Communication Skills: During interviews, take note of the candidate’s ability to explain complicated ideas, as this is essential for developing collaboration between departments.
• Problem-Solving: To assess a candidate’s problem-solving capabilities, talk about how they have solved previous issues and how they overcome them.
• Teamwork: To learn more about their capacity to operate in a group setting, ask them about their previous team efforts.

What are the Interview Tips to Hire Data Scientists?

• Prepare a list of questions covering a variety of abilities and experiences for structured interviews.
• Talk about past experiences to understand or forecast future behavior by asking candidates to explain them.
• Give them an issue to address in the corporate world and watch how they approach the topic strategically and creatively.

After this, you are just one step away from hiring data scientists, and the last piece of the puzzle is the important one- from where you should hire a talented candidate who has a strong hand on each skill of data science and who fits your requirements perfectly.

We have just the right platform for you. 

Hire Tech Talent’s Role in Helping Recruiters to Hire Data Scientists

Hire Tech Talent is a platform that uses a reverse recruitment method to transform the traditional method of hiring. This creative strategy aims to address the issues facing the rapidly expanding global tech sector, which is struck by a severe talent shortage.

The platform seeks to improve the effectiveness and efficiency of the hiring process from startups to enterprise-level companies.

How Hire Tech Talent Benefits Recruiters?

• Direct Opportunities: Recruiters can reach out to the tech talents directly based on their skills and expertise. This improves the efficiency and targeting of the job search.
• Pre-Screened Talent Profiles: Hire Tech Talent accurately matches recruiters’ needs with talent profiles and pre-screened them before shortlisting, recruiting the recruiter time and money. 
• Flexibility in Hiring: The platform allows recruiters to hire remotely or on-site, providing companies and candidates more flexibility.
• Complete Hiring Cycle Support: Hire Tech Talent offers help in the complete process of hiring to the recruiters, from finding applicants to setting up interviews to extending employment offers.
• Diverse Talent Pool: The platform offers tech talent profiles from different locations, from freshers to experienced and leadership-level talents as well.

Hire Tech Talent’s Hiring Process for Data Scientists

Hire Tech Talent is a smooth and effective platform and can present you with many talented data scientists for hiring while making sure both candidates and recruiters have a good experience.

Here’s how you can hire data scientists in just 08 simple steps:

Registration and Login:

• Register as recruiters on the Hire Tech Talent platform and sign up.

Profile Creation and Verification:

• Recruiters create a detailed profile outlining their company’s requirements, including job descriptions, skill sets, and other relevant information.
• Profiles are verified to maintain the company’s credibility.

Platform Demo:

• The Customer Success Manager reaches out and helps you under the working of the platform and how you can look for the talents that will exactly match your requirements.

• Recruiters also get help regarding the hiring process, including technical support or additional services.

Purchasing Plans:

• Recruiters select a suitable pricing plan based on their hiring needs, which may include options like number of job postings, number of hires, etc.

Requirement Analysis:

• Hire Tech Talent collaborates with recruiters to understand their specific requirements and preferences for data scientist roles.

Providing Pre-Screened Profiles:

• Based on the employer’s criteria, Hire Tech Talent presents pre-screened profiles of data scientist candidates who match the job requirements.

Shortlisting from the List:

• Recruiters review the profiles and shortlist candidates they wish to further evaluate or interview.

Sending Interview Requests to Candidates:

• Recruiters can send interview requests directly to shortlisted talents through the platform, scheduling meetings as needed.

Sending Custom Challenges to Candidates:

• Recruiters have the option to send custom challenges or assessments to candidates to evaluate their skills and suitability for the role.

Hiring if Skills Match the Job Requirement:

• Upon completing the interview process and evaluating candidates, recruiters can proceed with hiring the most suitable data scientist candidate if their skills align with the job requirements.

FAQ

• Describe the process of looking for a data science job?

During the job search process, you will need to network to connect with the right people at different companies, apply to multiple jobs via different channels, and prepare for interviews—even though the results of these are unpredictable—as well as schedule your interviews strategically to land the best position and pay. 

• What is the scope of DS in the job market? 

Numerous roles exist, such as data scientist, analyst, data engineer, and so forth. There are numerous company tiers. Larger organizations have more complex jobs, whilst smaller ones typically integrate several roles into one. The total demand is anticipated to rise over the next several years as more businesses begin their journey towards data. 

• What skills and qualities do recruiters look for in a data scientist?

Recruiters look for data scientists who are good at math, statistics, and computer science. They want people who can code, especially in Python or R, and use special tools for analyzing data. 

It’s important for a data scientist to solve problems, think clearly, and explain complex ideas in easy ways. They also like people who can show data in simple charts and keep learning new things. Being able to work well with others is a big plus. 

• Do recruiters search for a PhD in advanced machine learning? 

When applying for more senior positions, people usually look for several years of relevant experience or a specialist degree combined with some level of expertise. When seeking for a more senior post, recruiters usually look for candidates who have seen a variety of ML challenges and addressed them, as well as those who can think up the perfect answer for a brand-new problem.

In an entry-level position, a degree typically lends some credibility, but good projects and a strong portfolio can usually make up for it. In addition to the candidate’s ability to create code, recruiters also want to know if they are conversant with the fundamentals of machine learning.

Businesses that want to use data efficiently must hire data scientists and recruiters can easily find the right candidate by exactly understanding the role, thoroughly screening candidates, and using resources like Hire Tech Talent.

The reverse recruiting approach offered by this platform streamlines the hiring process by easily matching candidates with recruiters. If you want to explore more about Hire Tech Talent, Contact us today!