Data Scientist Job Description Template

November 30, 2020
Data Scientist Job Description Template

How To Write an Effective Data Scientist Job Description.

When you write a Data Scientist Job Description, keep the details relevant and concise. Also, focus on what your company needs by highlighting important skill sets and duties related to the job. 

Data Science is a vast and evolving field that differs greatly among industries. For instance, not every Data Scientist falls under the same category or does the same type of work. 

A Data Scientist from Apple might focus more heavily on strategic fraud prevention, while a Data Scientist from another company might focus on operational efficiency or building data-driven systems with the customer in mind.

When drafting the Data Scientist job description, think strategically about the outcome or goals your company needs to reach after hiring Data Scientist talent. Also, keep the job description concise and to the point. Also, don’t use unnecessary filler words or descriptors that other job postings commonly use. Finally, write a Data Scientist job description based on what you want this candidate to accomplish in the role.

What Does a Data Scientist Do?

The field of Data Science involves a wide range of technical skills. These skills range from massive experimental frameworks to implementing multi-armed solutions for headline optimization. Also, a large part of the role relies on the impact that machine learning has on business decisions and operational efficiency. Data Scientists have the responsibility of setting solid data foundation groundwork for companies. Their duties may vary from organization to organization, but for the most part, many are required to implement robust data analytics and build machine learning pipelines and personalized data products to better understand their customers. Essentially, Data Science is all about infrastructure, testing, machine learning, decisions making, and data products. Furthermore, remember that a Data Scientist role goes beyond the job description. Finally, the data scientist job description is just one part of the role on paper. 

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Copy this template, and modify it as your own:

Data Scientist Job Description Sample/Template

Are you an expert at your craft? Looking for a challenging new role where you can build new tech solutions, solve problems using complex data, and make a difference? 

Enrich your career today by joining a fast-paced and innovative work environment where you can take your technical and analytical data science skills to the next level. 

{{Copmany Name}} is looking for a data scientist that is a self-starter who can translate complex concepts and provide innovative solutions. 

We’re looking for a data scientist that can analyze and extrapolate large amounts of data, build innovative solutions, improve internal security measures, and advise on operational efficiency. If you are passionate about working in cross-functional teams and utilizing your skills for statistical analytics, data mining, predictive modeling, and creating a larger impact utilizing data science–consider applying to this role. 

You will be responsible for a variety of challenging projects that require constant communication and collaboration with data engineers and internal departments. Utilizing extensive database knowledge and programming skills, you will help build recommendation systems, implement A/B testing, research emerging technologies; develop testing procedures, and advise and implement fraud detection systems, among other day-to-day duties. 

As a part of this collaborative team, you will be responsible for overseeing and implementing complex, large-scale systems, and projects where you can utilize your data science techniques to improve customer experience and business efficiency. 

Responsibilities:

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
  • Combine models through ensemble modeling
  • Coordinate with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts.
  • Collaborate with product design and engineering to develop an understanding of needs
  • Research and devise innovative statistical models for data analysis
  • Communicate findings to all stakeholders
  • Enable smarter business processes—and implement analytics for meaningful insights
  • Keep current with technology and industry development
  • {{Select from the above and add other responsibilities that are relevant}}

Skills and Qualifications:

  • Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc {{depending on specific project requirements}}. Excellence in at least one of these is highly desirable
  • Great communication skills
  • Experience with data visualization tools, such as D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive, Pig {{actual list depends on what you are currently using in your company}}
  • Experience with NoSQL databases, such as MongoDB, Cassandra, HBase {{depending on project needs}}
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Good scripting and programming skills {{if you expect that the person in this role will integrate the solution within the base application, list any programming languages and core frameworks currently being used}}
  • Data-oriented personality
  • {{mention year of experience this candidate must have}}
  • {{mention the level of education this candidate must have}}
  • {{mention the experience this person must have outside of academia}}
  • {{mention the machine learning technologies; such as k-NN, Naive Beyes, SVM, Decision Forests, etc}}
  • {{mention technology the candidate will frequently use within the organization}}
  • {{list certifications you require}}

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