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Data Scientist Job Description Template (2026)
Understanding the Data Scientist Job Description
You don't need technical skills to write a data scientist job description. Hiring expert data scientists simply requires a thorough job description to communicate your expectations and cultivate interest in working for your organization. Learn how to write the best job description in 2026!
Your job description needs to stand out to attract data scientists. Demand for the role keeps climbing, largely because of how quickly companies are putting AI and machine learning to work. The U.S. Bureau of Labor Statistics now projects data scientist employment to grow 34% between 2024 and 2034, much faster than the average for all occupations, and ranks it the fourth-fastest growing job the agency tracks. In Canada, hiring is steadiest in tech hubs like Toronto, Vancouver, Montreal, and Calgary, where continued investment in AI, cloud, and analytics keeps demand for skilled talent high.
Creating a job description can be intimidating, so we'll start with a concrete example to demystify the elements of a good job description and identify the elements you'll need to customize. You can use our sample data scientist job description as a place to start, or as inspiration to develop your own. Our template is the best way to hire data scientists!
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The Data Scientist Job Description: A Detailed Example
A detailed example of a data scientist job description can be found below. We've filled in the details for illustrative purposes: be sure to tailor the details to the needs of your organization.
The specifics we've included target a "vanilla" data scientist with a few years of experience. Adjust the expectations, responsibilities, and skills if you intend to hire senior data scientists, staff data scientists, or data science managers.
You will need to consult your HR and legal departments to ensure compliance within your organization and within the laws of your geographic region.
Data Scientist
Start with key infoUpdated: January 12, 2026
Type: Full time
Locations: Toronto, Ontario, Canada; Remote
Salary range: CAD $95,000 - $135,000
Vacancy: Existing, open position
The Role
- Get them excited!We believe that data science can lead to insights that can guide the future of Awesome Inc.
As a Data Scientist at Awesome, Inc., you will analyze, design, and implement data solutions using our internal analytics tools. You will use your expertise in quantitative analysis, statistical modeling, and data visualization to see beyond the numbers and discover new insights that would have not been possible with traditional analytics.
You will leverage practical experience in applying varied data science techniques, domain experience, and offer advice to help with the design, development, and implementation of our products.
This position reports to the Director of Data Science.
Responsibilities
- Be clear and concise- Help build, design, and analyze experiments.
- Build key data sets to empower operational and exploratory analysis.
- Advocate for standard data collection, storage, and analysis methodologies across the organization.
- Own the definition, evaluation, visualization, and reporting of key product metrics.
- Partner with machine learning engineers to take promising models from prototype to production.
- Collaborate with our core team stakeholders of product, design, and engineering to inform, influence, and execute our product strategy.
- Make business recommendations and present findings to technical and non-technical stakeholders, including leadership.
Required Skills
List your tools- A background in Computer Science, Mathematics, Engineering, or a related field.
- Programming skills in Python or R.
- Ability to write clean, understandable code following leading industry standards.
- Knowledge of general Machine Learning concepts in theory and in application.
- Comfort working with data in a cloud environment, such as a major provider's data warehouse.
- Ability to consider biases that exist in the data, as well as develop and recommend solutions to mitigate biases appropriately.
- Strong interpersonal skills and the ability to communicate complex technical solutions to non-technical stakeholders.
- Ability to be open to many diverse voices and perspectives.
- The ability to extract data from a variety of sources using SQL or SQL-like tools.
- Curiosity and the excitement to continue your skills development.
Benefits
- We provide 3 weeks of time off and 10 sick days each calendar year.
- We provide paid parental leave (up to 26 weeks of fully paid leave for childbearing parents and up to 12 weeks for non-childbearing parents).
- Reimbursement of up to $2,000 per year for professional development.
About Awesome, Inc.
- Stand outAt Awesome Inc., we make awesome products come to life. Our products let millions of people lead their best, awesome lives. Join us in making their days extra awesome.
Diversity, Inclusion, and Equal Opportunity Employment
- ImportantAwesome Inc. is an equal opportunity employer: diversity and inclusion have always been at the core of our values. A diverse workforce with unique perspectives and creative ideas benefits our products, the communities where we operate, and all of us as colleagues. We welcome applications from qualified individuals from all backgrounds.
Awesome Inc. will ensure that all qualified individuals with disabilities are provided reasonable accommodations to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Legal and Data Privacy
Adjust as neededWe use applicant tracking software with AI-assisted resume screening as part of our hiring process. This posting is for an existing, open position. Any personal information you share while applying is handled in line with our privacy policy and applicable data protection laws. Reasonable accommodation is available where required by law.
Data Scientist Job Description Sections
Each of the sections are equally important. Use the details below to take a deeper dive and tailor the template to your organization.
Key Information
Start your job description with key information. Candidates need this to determine if your role is a viable fit. It will save you time if incompatible candidates filter themselves out. Common details to include are the posting date, the type of role (full-time, part-time, or contract), where the employees are able to work (including hybrid locations), and salary ranges. For more details on data scientist compensation and salary levels in Canada, check out our salary guide.
If you're hiring in Ontario, salary disclosure is now a legal requirement rather than a courtesy. As of January 1, 2026, employers with 25 or more staff must include the expected pay, or a pay range no wider than $50,000, in publicly advertised postings, with an exemption for roles paying above $200,000. British Columbia, Prince Edward Island, and several other provinces have their own pay transparency rules, so confirm the requirements wherever you hire.
The Role
Details about the role are critical, and they serve two purposes. The first purpose is to summarize what the job will entail. The second purpose is to get applicants excited about working for you. Enticing candidates with the role description will increase your number of applicants, and with the right pitch, can entice overqualified candidates to take a pay cut to work for you. Include who new employees will report to: this is a signal for the level of responsibility of the role.
Think about what makes your organization unique. For example, if the position is with a large organization, the sheer volume of data may mean there are lots of interesting opportunities to analyze it. For a smaller organization, candidates may find it exciting to be involved in laying the foundation of how your team collects and uses data to grow.
Responsibilities
Data scientist job responsibilities are important to communicate to prospective candidates, as different companies have different expectations. Describe what your ideal candidate would accomplish working for you. You'll want to cover the core day-to-day responsibilities, the expected products of their work, and how you want them to interface with the team.
This section is most valuable to candidates when it is concisely presented, and thoroughly captures the expectations of the role.
Required Skills
The required skills section is another opportunity for candidates to understand if they would be a good fit. This can be a chance for poor candidate matches to filter themselves out of the process, and can be an opportunity to showcase any interesting technologies that your team has available.
Capture required qualifications in a list.
Once you've identified data scientist skills and responsibilities, you can include information about why your company is an appealing place to work.
Benefits
Showcase your company's benefits and perks. Include necessities, like vacation time. Prospective employees will want to see if the intangible value of working for your organization matches their needs and hopes for work-life balance.
Creative benefits can also set your company apart. For example, famously, companies like Google and Facebook have offered a free food benefit. When compared with the yearly salary of tech employees, the allure of free food is a relatively cheap way to entice and retain staff.
Providing benefits that support your company's identity can be effective. For example, if your company works in the health space, providing benefits relating to exercise or a healthy lifestyle can be unique. Unique benefits can be a disproportionate draw and brand your company as cool.
About Your Company
Give your candidates the hard sell. Tell them why you're amazing, what sets you apart, or why you're poised for growth. You want candidates to picture themselves working for you and being excited at the prospect.
Diversity, Inclusion, and Equal Opportunity Employment
A statement on diversity, inclusion, and equal opportunity employment is standard practice. Review this section with your human resources (HR) and legal departments to ensure you are complying with company guidelines and applicable laws in your region.
Legal, Privacy, and Compliance
Your legal, privacy, and HR teams may recommend extra language in the posting. In Ontario, postings covered by the 2026 rules must state whether artificial intelligence is used to screen, assess, or select applicants, and whether the posting is for a genuine, existing vacancy rather than a pipeline of future candidates. The same rules also prohibit asking for prior "Canadian experience." Data privacy expectations differ by sector and region, so be clear about how candidate information is collected and stored. Run the final wording past HR and legal to confirm it complies with the laws that apply to you.
Job Description A/B Testing
Woohoo! The job description is done and you're ready to accept applications. To receive as many applications as possible, you should consider A/B testing. This is an advanced approach that will be more valuable for larger organizations. Smaller organizations may not receive enough applicants to make A/B testing worthwhile.
A/B testing is a method of running experiments to optimize your product. In the context of a job description, it means when a prospective job applicant visits your site, some of the users will see "job description version A" and some of the users will see "job description version B". You then measure the number of applicants that apply to each version. You can then use data science to analyze the number of applicants to each version of the job posting to determine which one is more effective.
Over time, A/B testing allows you to test different titles, headers, and copy. Keep trying different variations of your job description to discover what works best!
Next Steps
Post a job on DataScienceJobsCanada.com to reach talented data scientists, data analysts, machine learning engineers, and AI researchers. Our enthusiastic followers will supercharge your data and invigorate your team: post a job now to receive more resumes!
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