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Data Scientist Job Description: How to Hire Data Science Experts in 2022

How to Hire Data Scientists and Find Experts Fast


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 2022!

Your job description needs to stand out to attract data scientists. Demand continues to rise rapidly. Coming in to 2022, demand for data science experts had skyrocketed 295%! According to the U.S. Bureau of Labor Statistics, the job outlook for data scientists is set to grow "much faster than average", at 36%. In Canada, future job prospects for data scientists are high across the country.

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. Use our template to hire the best data scientists!

Already have a data scientist job description? Post your job now!


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 info

Posted date: October 15, 2022
Type: Full time
Locations: Toronto, Ontario, Canada; Remote


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.
  • 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.
  • 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 out

At 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

  - Important

Awesome 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, COVID, Data Privacy

   Adjust as needed

Awesome Inc. requires as a condition of employment that all successful candidates in and Canada be fully vaccinated against COVID-19 prior to their start date. Awesome Inc. may require proof of vaccination. 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.

The Role



Details about the role are critical and serves 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 overqualitifed 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



Describe what your ideal candidate would accomplish working for you. You'll want to cover the core day to day responsibilites, 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.

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 a 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, COVID, Data Privacy



Legal, health, and privacy departments may recommend additional information to be included in your data scientist job posting. Some candidates will want to know safety protocols relating to COVID. Do your due diligence in complying with your regional standards.


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 user 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!

Join our mailing list and follow us on social media for more analysis and to hear about exceptional opportunities across Canada. Send us a message on social media or at datasciencejobscanada@gmail.com if you've enjoyed this guide or have any suggestions to improve it!

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