Data Science

Data Scientist Job Description Template

A data scientist is someone who makes value out of data. Such a person proactively fetches information from various sources and analyzes it for better understanding about how the business performs, and builds AI tools that automate certain processes within the company.

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A data scientist is someone who makes value out of data. Such a person proactively fetches information from various sources and analyzes it for better understanding about how the business performs, and to build AI tools that automate certain processes within the company.

There are many definitions of this job, and it is sometimes mixed with the Big Data engineer occupation. A data scientist or engineer may be X% scientist, Y% software engineer, and Z% hacker, which is why the definition of the job becomes convulted. The actual ratios vary depending on the skills required and type of job. Usually, it’s considered normal to bring people with different sets of skills into the data science team.

Data scientist duties typically include creating various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems. People within this role should also be able to perform statistical analysis.

In this article, we present a sample data scientist job description, for you to adjust depending on your actual needs to create a perfect job advertisement, and to find the person that will help you get the answers you are looking for.

Data Scientist - Job Description and Ad Template

Copy this template, and modify it as your own:

Company Introduction

{{Write a short and catchy paragraph about your company. Make sure to provide information about the company culture, perks, and benefits. Mention office hours, remote working possibilities, and everything else you think makes your company interesting. Data scientists like to take challenges - anything that shows how the role could make an impact might help attract top talent.}}

Job Description

We are looking for a data scientist that will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. {{Depending on your needs, you can write very specific requirements here, like: “automate scoring using machine learning techniques”, “build recommendation systems”, “improve and extend the features used by our existing classifier”, “develop internal A/B testing procedures”, “build system for automated fraud detection”, etc.}}

Responsibilities

  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Extending company’s data with third party sources of information when needed
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated anomaly detection systems and constant tracking of its performance
  • {{Select from the above and add other responsibilities that are relevant}}

Skills and Qualifications

  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • 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 visualisation 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 any other technology that such person is going to commonly work with within the organization}}
  • {{List education level or certification you require}}

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