Data Scientist Job Description Template

Data Scientists are data experts that use their technical and analytical skills to create value out of complex data. Their job is to fetch and store information from a variety of sources and then use statistics and maths to derive insights from it, often about business performance or emerging trends. They’re part mathematician, part computer scientist and part trend-spotter. Also building machine learning tools to facilitate certain business processes are part of their repertoire.


Data Scientists are data experts that use their technical and analytical skills to create value out of complex data. Their job is to fetch and store information from a variety of sources and then use statistics and maths to derive insights from it, often about business performance or emerging trends. They’re part mathematician, part computer scientist and part trend-spotter. Also building machine learning tools to facilitate certain business processes are part of their repertoire.

The job title itself is ambiguous as it includes a wide range of people and skills. A Data Scientist relies on mathematical, data analyst and software engineering skills so it is up to you to decide which qualities you are looking for when hiring one. You need to make a clear distinction in your description as the profession is often conflated with Big Data Engineering. Often you will have to bring together a team from the data science field to have a full range of skills across the board. However you need to look for people with strong statistical analysis skills to create different machine learning based tools or processes.

This template will help you write the right job description for a Data Scientis and find the perfect specialist that can pull the right data for you from a huge value’s pool.


Company Introduction

[Start your job description with a convincing and engaging pitch of of your company. Let the candidate know about your mission, working culture, perks and benefits (like opportunities to work remote) and your corporate social responsibilitiy activities. Extra tip: If you are hiring into an existing team, include an "Meet your new team" section that introducces the team your new hire would join, inlucding it's role within the company, and the team's working style.]

Job Description

We are looking for a Data Scientist that will use his skill set to help us make good decisions by finding the right insights from vast amounts of data. You will help us improve our products with the right statistical analysis, data mining techniques and prediction systems. (Here you can get very specific on what your project’s requirements are, examples of which could be - Automate scoring using machine learning techniques - create recommendation systems - develop internal A/B testing procedures - improve and extend the features used by our existing classification system -build system for automated fraud detection etc.)

Responsibilities

  • Decide on features, develop and optimise classifiers using machine learning
  • Data mining/analysis using best practice and state of the art methodology
  • Extend the reach of in-house data using information from third-party sources.
  • Improving data collection procedures to use information that is relevant for building analytic systems
  • Processing, cleaning, and assuring the integrity and validity of data used for analysis
  • Doing ad-hoc analysis and presentation of results in a concise way
  • Creating automated anomaly detection systems and constant tracking of its performance

  • Choose which of the above responsibilities best fit your project and add other relevant ones

Required Skills & Qualifications

  • Proficiency at machine learning approaches and algorithms like k-NN, Naive Bayes, Decision Forest, SVM and etc.
  • Good knowledge of how to use data visualisation tools like D3.js and GGplot (if visualization toolset is decided specify here)
  • Prior experience with a NoSQL database like Cassandra, MongoDB or Lucene/SOLR (adapt to project needs)
  • Hands-on knowledge of using query languages like Hive, SQL, Pig for analysis (adapt for what is currently in use in-house if applicable)
  • Strong proficiency with at least one or more popular data science toolsets like NumPy, R, MatlAB, Weka, etc. (select applicable toolsets if known)
  • Comfortable using various statistical methods (such as statistical testing, distributions, regression etc.) for pulling the right information from data
  • Know how to program and write scripts (depending your project requirements write what languages you are looking for)
  • Have good communication skills and be a natural when it comes to thinking data

  • Add any other technologies and methods that the candidate will work with your project

  • Add qualification requirements