How to become Data Scientist in 2024

Data Scientist Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

Data Scientist is Also Know as

In different settings, Data Scientist is titled as

Education and Training of Data Scientist

Data Scientist is categorized in Job Zone Four: Considerable Preparation Needed

Experience Required for Data Scientist

A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.

Education Required for Data Scientist

Most of these occupations require a four-year bachelor's degree, but some do not.

Degrees Related to Data Scientist

Training Required for Data Scientist

Employees in these occupations usually need several years of work-related experience, on-the-job training, and/or vocational training.

Related Ocuupations

Some Ocuupations related to Data Scientist in different industries are

What Do Data Scientist do?

  • Analyze, manipulate, or process large sets of data using statistical software.
  • Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
  • Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.
  • Clean and manipulate raw data using statistical software.
  • Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
  • Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
  • Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
  • Design surveys, opinion polls, or other instruments to collect data.
  • Identify business problems or management objectives that can be addressed through data analysis.
  • Identify relationships and trends or any factors that could affect the results of research.
  • Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
  • Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
  • Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.
  • Recommend data-driven solutions to key stakeholders.
  • Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
  • Write new functions or applications in programming languages to conduct analyses.

Qualities of Good Data Scientist

Tools Used by Data Scientist

Technology Skills required for Data Scientist

  • Alteryx software
  • Amazon Elastic Compute Cloud EC2
  • Amazon Redshift
  • Amazon Simple Storage Service S3
  • Amazon Web Services AWS SageMaker
  • Amazon Web Services AWS software
  • Apache Airflow
  • Apache Cassandra
  • Apache Hadoop
  • Apache Hive
  • Apache Kafka
  • Apache MXNet
  • Apache Pig
  • Apache Spark
  • Atlassian Confluence
  • Atlassian JIRA
  • Bash
  • BigQuery
  • Business intelligence software
  • C
  • C#
  • C++
  • Docker
  • Elasticsearch
  • Flask
  • Geographic information system GIS systems
  • Git
  • GitHub
  • Go
  • Google Cloud software
  • Google Looker Analytics
  • IBM SPSS Statistics
  • JavaScript
  • JavaScript Object Notation JSON
  • Jenkins CI
  • Julia
  • Jupyter software
  • Keras
  • Kubeflow
  • Kubernetes
  • Linux
  • Management information systems MIS
  • MapReduce big data software
  • Mathematical software
  • Microsoft Access
  • Microsoft Azure software
  • Microsoft Excel
  • Microsoft Office software
  • Microsoft Power BI
  • Microsoft PowerPoint
  • Microsoft SQL Server
  • Mlflow
  • MongoDB
  • Neo4j
  • NoSQL
  • NumPy
  • Oracle Java
  • pandas
  • Perl
  • PostgreSQL
  • PySpark
  • Python
  • PyTorch
  • Qlik Tech QlikView
  • R
  • Reporting software
  • RESTful API
  • Ruby
  • SAS
  • Scala
  • Scikit-learn
  • SciPy
  • Shell script
  • Shiny
  • spaCy
  • Splunk Enterprise
  • StataCorp Stata
  • Statistical software
  • Structured query language SQL
  • Tableau
  • TensorFlow
  • Teradata Database
  • The MathWorks MATLAB
  • UNIX
  • XGBoost