Data Scientist Job Description, Key Duties and Responsibilities
This post provides complete information of the job description of a data scientist to help you learn what they do.
It highlights the key duties, tasks, and responsibilities that commonly make up the data scientist work description in most organizations.
It also presents the major requirements most recruiters will ask applicants for the data scientist position to meet to be considered for the job.
Please, continue reading to learn more about the data scientist career:
What Does a Data Scientist Do?
The data scientist enables organizations with large volume of data to make optimal use of it for better business decisions. They are responsible for gathering information from multiple sources about a business, and analyzing it for better understanding about how it performs.
They also build AI tools that automate certain processes within the company.
The data scientist job description entails participating in activities across the data science lifecycle: business case definition, data collection, and cleaning; integration, analysis, and visualization; feature engineering, modeling with machine learning algorithms, and interpreting the models/results, and reporting.
Data scientists are also required to work collaboratively with product managers, software engineers, and analytical groups, and customer-facing teams in an agile environment.
They are responsible for designing actionable data products based on statistical analysis and machine learning methods, and also deploy them to enterprise systems.
They utilize state-of-the-art techniques, e.g. cluster analysis, natural language processing, and pattern recognition; pictured-imagination and other methods that can be used to capture data, mine in, and effectively manage it, and then properly analyze it.
The data scientist work description also involves improving statistical, mathematical, or machine learning models to forecast results, which might include linear regression models and random forest utilization.
It also includes communicating data findings to stakeholders using different visual formats to picture and give reports; accumulate and render difficult information for audiences at stages of technical knowledge that varies.
Data scientists are responsible in creating various machine learning-based tools or processes such as recommendation engines or automated lead scoring systems, etc. within an organization.
They typically work with data processing pipelines for analyzing gigabyte to terabyte scale data from multiple sources and obtain insights that will drive the decisions that power an organization’s platform.
Data Scientist Job Description Example/Sample/ Template
Data scientists perform various functions, including utilizing modern data science techniques to examine, explain, and interpret data sets, and to recognize and forecast trends, as well as conduct analytics concerning activities that are important to the organization.
The data scientist job description in most organizations usually consists of the following core tasks, duties, and responsibilities:
- Responsible for executing statistical methods to solving specific business problems
- Responsible for developing new data sources, testing model enhancements, and fine-tuning model parameters to improve upon existing methodologies
- Take active part in the design and development of automated forecasting systems
- Responsible for the construction of customer-facing reporting tools to provide insights and metrics which track forecast
- Ensure that the models are well developed, tested, trained, and implemented
- Ensure that the integrity and dependability of data for analytical purposes are processed, cleansed and verified
- Decide features for data extraction, which might include the construction and optimization of classifiers utilizing machine-learning methods
- Responsible for the accurate exploration of internally and externally sourced data to search for unseen insights and correlation
- Responsible for data management for constructing analytic systems
- Strongly supports the adoption of data science and well improved analytics across the whole organization, and also at managerial, executive, and operational stages.
Data Scientist Job Description for Resume
If you have worked before as a data scientist or are presently working in that role and are preparing a resume for another job, you can quickly create the professional or work experience section by adopting the above job description.
You can apply the data scientist duties and responsibilities highlighted in the above job description in completing the work experience part of your resume to show the recruiter that you have or are actually performing the functions of the role.
Data Scientist Requirements – Skills, Knowledge, and Abilities for Career Success
If you are seeking the job of a data scientist, most recruiters will expect you to meet certain requirements to qualify you to access the position.
This is to help the recruiter to attract only candidates who can effectively perform the obligations, purpose, and objectives of the data scientist role in their organization.
Shown below are major requirements you may be asked to fulfill if you are seeking the job of a data scientist:
- Education: Applicants for the data scientist job are commonly required to have a minimum of Bachelor’s degree in Computer Science, Engineering, or Statistics, or in any other quantitative field. However, a Master’s degree is preferred
- Knowledge: They should have solid understanding of popular machine learning algorithms and latest and newly emerged statistical, visualization, extraction and algorithmic methods. Employers seek individuals with proficiency in at least one statistical software package such as R, Stata, Matlab, or Python; experience with object-oriented programming languages; as well as expertise using SQL for acquiring and transforming data from relational databases
- They must also have outstanding understanding of quantitative modeling and statistical analysis and experience building complex data visualizations for business stakeholders using a variety of visualization tools, including MS Excel and libraries in R/Python
- Collaborative skills: The data scientist job requires them to work directly with economists and statisticians to produce modeling solutions. They also partner with software developers and data engineers to build end-to-end data pipelines and production codes, etc. So it is crucial that applicants can work effectively with people of varied background to achieve project goals
- Statistical analysis skills: It is important that applicants can manage difficult statistical/predictive models. They must be able to perform analysis on complex problems, translate the needs of operation, and enhance combined creative solutions
- Problem Solver: It is important that applicants enjoy diving into data; can resolve difficult modeling and analytical challenges, and possess decision making skills to proffer solutions to business problems
- Communication skills: It is essential that applicants possess strong communication skills, including verbal and written communication abilities to effectively interface between technical and business teams. It is also crucial for them to pass technical information to a non-technical audience.
If you are a recruiter or HR manager needing to hire for the data scientist position in your organization, you can apply the sample job description shown above in making the description that perfectly fit the role in your organization.
It is important to also publish the description of the data scientist role in addition to the vacancy advertisement to inform prospective candidates of what the role entails.
This will help to ensure that only candidates who can effectively perform the data scientist role in your organization are the ones to apply, thereby helping you to find quality candidates for the position.
This post is also useful to individuals interested in the data scientist career to learn all they need to know about what the role does.