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Data Scientist Job Description Template

A top-notch Data Scientist job description is your first chance to attract top talent. Drawing from interviewing and hiring thousands of engineers, Terminal's developer job description template library can help you target the right make a great first impression.

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Data Scientist Job Description

Data scientists collect, organize, and draw insights from large datasets using mathematical and statistical techniques. They often interact heavily with machine learning and artificial intelligence tools to predict outcomes and assist decision-making.

Data science is a broad field, and data scientists typically specialize in different areas. Job description templates help you narrow your search criteria and filter for suitable candidates.

Data Scientist Job Description Template

We are looking for professional data scientists who can effectively extract and manage data from various sources. This role demands excellent communication skills since you will create visualizations and present your findings to key stakeholders.


Ideal candidates for this position must be able to think independently and solve complex problems. They must also have sufficient knowledge of Python or R, mathematics, and statistics.

About the Company

[Company], founded in [year], is a [type of business] that [what you do]. We value diversity and equality, which is reflected in our highly inclusive and collaborative work environment. Our corporate vision is [vision statement].

At [Company], we offer you the opportunity to add value at a rapidly growing organization, develop your skills, and make meaningful connections with other exceptional talents.

Job Responsibilities

- Study business problems and suggest data-driven solutions to enhance decision-making
- Analyze big data to identify patterns and trends
- Create algorithms for predictive analysis
- Select and deploy machine learning models for projects
- Document reports and create compelling visualizations
- Improve data collection methods and ensure the accuracy of data sources
- Perform data cleaning
- [Insert any others…]


Must Have Qualifications

- [–] years of experience in a similar data scientist role
- Strong understanding of core mathematical concepts (e.g., algebra, calculus, and probability)
- Ability to code in R or Python Knowledge of relational and non-relational database management
- Experience with Excel, PowerPoint, and Tableau
- Proficiency with popular machine learning tools and ability to conduct predictive modeling
- [Insert any others…]

Nice to Have Qualifications

- Bachelor’s degree or higher in computer science, software development, information technology, or similar fields.
- Superb time management skills.
- Exceptional critical thinking skills.
- Ability to collaborate effectively.
- [Insert any others…]

Sections of a Data Scientist Job Description

  • Data Scientist Job Description Overview
  • Data Scientist Job Titles
  • About the Company
  • Data Scientist Job Responsibilities
  • Must-have Skills and Qualifications
  • Nice-to-have Skills and Qualifications
  • Salary, Benefits, and Perks

Data Scientist Job Description Overview

Data is the bedrock of modern-day businesses. Globally, companies rely on technology to convert their large datasets into insights for decision-making. This need has led to the evolution of the data scientist role in most organizations.

Data scientists use data to solve problems. They are responsible for gathering, cleaning, and analyzing information from various sources to create visualizations, identify significant relationships between data points, and make predictions.

Data scientist roles vary in complexity from one organization to another. Depending on the company, data scientists may be required to build algorithms, perform data mining, and train machine learning models. However, regardless of their role, most data scientists often use visuals, charts, and reports to create compelling stories that stakeholders can understand.
When hiring for a data scientist role, it is important to use a job description template that clearly defines the available job title, responsibilities, skills, and salary.

Data Scientist Job Titles

Applicants first look at the job title before deciding to proceed with the rest of the job description. Job titles also play a massive role in enhancing the discoverability of an opening. Furthermore, you should specify whether you’re hiring for an entry, mid-level, or senior position.

Your job title must be clear, straightforward, and incorporate popular keywords. SEO optimization is critical if you want your job posting to appear at the top of search engines and job boards. Find common keywords among the top search results for similar job postings and incorporate them into your title description.

An excellent job title should be written with a focus on potential applicants. This means you must avoid using internal references that outsiders may not understand. Also, it is wise to avoid including abbreviations unless they are widely known and accepted. 

Sample Job Titles for Data Scientist:

- Data Scientist I
- Data Scientist II
- Machine Learning Scientist

About the Company

Here, you should explain to the candidate why your company is an attractive destination for top talent. Briefly discuss your value proposition, unique selling points, and company culture. Mention your industry and let the potential candidates know what they stand to gain by working with you.

Sample Company Description:

[Company], founded in [year], is a [type of business] that [what you do]. We value diversity and equality, which is reflected in our highly inclusive and collaborative work environment. Our corporate vision is [vision statement].

At [Company], we offer you the opportunity to add value at a rapidly growing organization, develop your skills, and make meaningful connections with other exceptional talents.

Data Scientist Job Responsibilities

Before applying, candidates typically examine the outline of job responsibilities to determine if they can carry out the listed responsibilities. This part of the template is important because it sets the tone for future performance evaluations after employment.

After providing a general overview of the role in the description section above, you can outline the job's major responsibilities in more detail here. Presenting these tasks in a bulleted-point format is usually best for easy readability. Also, aim to keep the language simple and avoid unnecessary jargon.

Depending on the nature of the role, employees may be required to architect and develop solutions, create documentation for software programs, work in a distributed team, perform system testing and quality assurance practices, and more.

Your job description may also include other aspects, such as frequent presentations to stakeholders and participation in brainstorming sessions with other team members.

Sample Job Responsibilities for Data Scientist:

- Study business problems and suggest data-driven solutions to enhance decision-making
- Analyze big data to identify patterns and trends
- Create algorithms for predictive analysis
- Select and deploy machine learning models for projects
- Document reports and create compelling visualizations
- Improve data collection methods and ensure the accuracy of data sources
- Perform data cleaning
- [Insert any others…]

Must-have Skills and Qualifications

Every job role has non-negotiable requirements for success, commonly referred to as “must-have skills.” Using simple and concise language, outline any mandatory prerequisites (if available), such as education, certifications, technical skills, programming languages, software competencies, and work experience.

Sample Must-have Qualifications for Data Scientist:

- [–] years of experience in a similar data scientist role
- Strong understanding of core mathematical concepts (e.g., algebra, calculus, and probability)
- Ability to code in R or Python Knowledge of relational and non-relational database management
- Experience with Excel, PowerPoint, and Tableau
- Proficiency with popular machine learning tools and ability to conduct predictive modeling
- [Insert any others…]

Nice-to-have Skills and Qualifications

Nice-to-have qualifications are not mandatory for stellar on-the-job performance. However, these skills are an added advantage for candidates who possess them. They allow candidates to distinguish themselves from the rest of the pack and increase their chances of landing a job.

In this section, you can briefly state any non-mandatory qualifications for your job posting.


Sample Nice-to-have Qualifications for Data Scientist:

- Bachelor’s degree or higher in computer science, software development, information technology, or similar fields.
- Superb time management skills.
- Exceptional critical thinking skills.
- Ability to collaborate effectively.
- [Insert any others…]

Salary, Benefits, and Perks

Times have changed, and companies are now more open to disclosing their remuneration rates in job postings. According to data from Indeed.com, up to 50% of recent job ads now include salary information. In this era of increasing pay transparency, being open about how much you’re willing to pay for the listed role is not out of place.

Here, you can highlight your monthly or yearly pay as well as other special benefits offered by your company. This is your chance to detail the core benefits your company provides, such as health, dental, and vision care, retirement plans, equity, stock options, or paid holidays.

In addition to this, you can list any other perks and benefits like meals, work-from-home stipends, fitness reimbursements, mental health programs, career development opportunities, sabbaticals, and more.

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Data Scientist interview questions

Looking for a comprehensive list of interview questions to evaluate a Data Scientist ? We've got you covered! Check out our list of 15 detailed and insightful interview questions for Data Scientist.

View Interview Questions

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