Data Scientists

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.

SOC: 15-2051.00

What You'll Need to Succeed

AI-generated

Key competencies for this occupation at a glance

  • KnowledgeDesign machine learning models and natural language processing algorithms using Python, R, TensorFlow, and PyTorch to extract insights from large structured and unstructured datasets.
  • KnowledgeCreate interactive data visualizations and dynamic reporting dashboards using Tableau, Power BI, and Python libraries to communicate findings to technical and non-technical stakeholders.
  • KnowledgeSynthesize insights from multiple data sources and analytical methods to formulate data-driven recommendations that address complex business problems.
  • KnowledgeAnalyze large-scale data patterns and statistical relationships applying data mining and data modeling techniques across distributed computing environments.
  • Hands-onOperate big data processing frameworks including Apache Spark, Hadoop, and Kafka to transform raw data into analytical datasets.
  • KnowledgeDevelop data pipelines and ETL workflows using cloud platforms such as AWS, Azure, and Google Cloud with containerization tools like Docker and Kubernetes.
  • Hands-onExecute complex SQL queries and database operations across relational and NoSQL databases including PostgreSQL, MongoDB, and Cassandra.
  • KnowledgeEvaluate model performance metrics and predictive accuracy applying statistical validation techniques and A/B testing methodologies in production environments.
  • Hands-onManipulate multidimensional datasets using programming libraries including pandas, NumPy, and scikit-learn for feature engineering and data transformation.
  • MindsetIntegrate ethical data practices and privacy considerations when designing analytics solutions that handle sensitive or personally identifiable information.
  • KnowledgeImplement version control and collaborative development workflows using Git, GitHub, and CI/CD tools like Jenkins to maintain reproducible analytics code.
  • MindsetAdvocate data-driven decision-making and analytical rigor when collaborating with cross-functional teams and presenting findings to executive leadership.
Wage Data According to the Bureau of Labor Statistics

Annual wage data for Data Scientists (2024)

Estimated Total Employment (U.S.)

233,440

Wage Distribution by Percentile

MetricU.S.
10% of workers earn the following or less$63,650
10% of workers earn the following or more$194,410
Workers on average earn$124,590

+ indicates wage is at or above the BLS reporting cap ($239,200/year)

Tools & Technology

Equipment and software commonly used in this occupation

In-Demand Technology

Frequently requested by employers in job postings

Alteryx softwareAmazon Elastic Compute Cloud EC2Amazon RedshiftAmazon Simple Storage Service S3Amazon Web Services AWS softwareApache CassandraApache HadoopApache HiveApache KafkaApache SparkAtlassian ConfluenceAtlassian JIRABashCC#C++DockerElasticsearchGitGitHubGoIBM SPSS StatisticsJavaScriptJavaScript Object Notation JSONJenkins CIKubernetesLinuxMicrosoft AccessMicrosoft Azure softwareMicrosoft ExcelMicrosoft Office softwareMicrosoft Power BIMicrosoft PowerPointMicrosoft SQL ServerMongoDBNoSQLOracle JavaPerlPostgreSQLPyTorchPythonRRubySASScalaShell scriptSplunk EnterpriseStructured query language SQLTableauTensorFlowTeradata DatabaseThe MathWorks MATLABUNIX

Technology Skills

Amazon Web Services AWS SageMakerApache AirflowApache MXNetApache PigBigQueryBusiness intelligence softwareFlaskGeographic information system GIS systems