Occupation · SOC 15-2051
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.
Median wage
$112,590
$63,650–$194,410
Projected growth
+33.5%
Faster than average
Annual openings
8,250
per year
Employed (US)
233,440
Job Zone 4
Typical preparation
Considerable preparation
Stackable credential programs
3,383 mapped
Core skills
Critical ThinkingReading ComprehensionActive ListeningComplex Problem SolvingSpeakingJudgment and Decision MakingWritingActive Learning
Knowledge areas
Computers and ElectronicsEnglish LanguageMathematicsEngineering and TechnologyCustomer and Personal Service
Technology & tools
Business intelligence and data analysis softwareData base user interface and query softwareStorage networking softwareCloud-based management softwareProcedure management software
Representative tasks
Troubleshoot program and system malfunctions to restore normal functioning.Provide staff and users with assistance solving computer-related problems, such as malfunctions and Test, maintain, and monitor computer programs and systems, including coordinating the installation o
Competency framework
Skill expectations by proficiency level.
emerging
Structured datasets and query tools — retrieve and inspect using standard SQL commands under direct supervisor guidance in a business analytics environment.Program malfunctions and error logs — identify and document following established troubleshooting checklists on assigned data pipelines.Business intelligence dashboards — interpret pre-built visualizations and summarize findings in written reports for team review.Statistical software and development environments — execute provided scripts and record outputs under close mentorship during onboarding projects.Data quality issues and anomalies — recognize and escalate using defined protocols within a structured data governance workflow.Database management systems — navigate and perform basic queries following documented procedures on production or staging environments.Computer program installation and configuration — assist senior staff in coordinating and testing setup steps according to written runbooks.Technical findings and data summaries — communicate clearly in team meetings using active listening and structured speaking techniques.Mathematical and statistical concepts — apply foundational methods such as descriptive statistics to support routine analytical tasks assigned by senior data scientists.Cloud-based management tools — operate under direction to monitor resource usage and flag irregularities for supervisor review.
developing
Recurring data pipeline malfunctions — diagnose and resolve with reduced oversight by applying systematic debugging techniques in production environments.Business problems involving integrated data sources — analyze independently using business intelligence software to develop actionable solution recommendations.Computer programs and automated workflows — test, maintain, and monitor on a scheduled basis, adapting procedures when standard approaches prove insufficient.Staff and end-user data-related inquiries — address by providing clear, accurate assistance on database tools and analytical software in a service-oriented setting.Moderately complex datasets from multiple systems — join, transform, and model using SQL and scripted environments to support departmental decision-making.Project timelines and analytical deliverables — manage using project management software, coordinating tasks with cross-functional stakeholders independently.Analytical findings and methodology — document in written technical reports that meet organizational standards for clarity and reproducibility.Statistical and machine learning models — build and validate in familiar problem contexts, adjusting hyperparameters based on performance metrics.Data storage and cloud infrastructure configurations — maintain and troubleshoot using storage networking and cloud-based management software with limited supervision.Emerging tools and analytical techniques — evaluate through active learning and apply selectively to improve existing workflows within established team practices.
proficient
Complex, non-routine system and program malfunctions — diagnose root causes autonomously and implement durable fixes across interconnected data systems in enterprise environments.End-to-end analytical solutions for strategic business problems — design and deliver, integrating data from disparate sources using advanced modeling and business intelligence platforms.Machine learning and predictive models — develop, deploy, and monitor at full production scale, exercising independent judgment on algorithm selection and validation strategy.Data infrastructure spanning databases, cloud services, and storage networks — architect and optimize to ensure reliability, performance, and security across the organization.Ambiguous, high-stakes analytical questions — frame, investigate, and resolve by applying inductive and deductive reasoning across novel data environments.Cross-functional teams and senior stakeholders — advise by translating complex quantitative findings into accessible recommendations through expert oral and written communication.Procedure management and content workflow software — configure and govern to standardize data science processes and ensure consistency of analytical outputs.Ethical, legal, and technical risks in data projects — evaluate with high attention to detail and integrity, applying cautious judgment before deployment decisions.Custom analytical tools and automation scripts — engineer independently within development environments to accelerate team productivity on recurring research tasks.Organizational data literacy gaps — assess and address by designing training materials and knowledge-sharing sessions that build analytical capability across user groups.
advanced
Enterprise-wide data science strategy and capability roadmap — define and champion, aligning analytical investments with long-term organizational objectives across all business units.Organizational standards for model development, validation, and governance — establish and enforce, setting the technical direction that all data science practitioners follow.Senior data scientists and cross-disciplinary teams — mentor and develop through structured coaching, performance feedback, and deliberate career growth planning.Novel methodological approaches and innovative tool adoption — lead evaluation and institutionalization of, driving competitive differentiation through intellectual curiosity and calculated risk-taking.Executive leadership and board-level stakeholders — advise by synthesizing complex analytical insights into strategic narratives that directly inform high-impact business decisions.Partnerships with engineering, product, and domain leadership — orchestrate to embed data science solutions into core operational and product development workflows at scale.Organizational risk posture for data, privacy, and algorithmic accountability — shape by developing policies and oversight mechanisms grounded in integrity and regulatory compliance.Large-scale system overhauls and data platform modernizations — sponsor and govern, ensuring technical excellence and business continuity throughout multi-year transformation programs.Talent acquisition pipelines and workforce development programs for data science — design and lead, ensuring the organization attracts and retains top-tier analytical professionals.Firm-wide culture of evidence-based decision-making — cultivate by modeling rigorous critical thinking and championing data-driven practices at every level of the organization.
Also known as
34 alternate job titles map to this occupation.
Quantitative MethodologistData Visualization DeveloperCryptanalystData Analytics ScientistStatistical ConsultantData Analytics SpecialistData AnalystData SpecialistData Analytics ManagerApplied ScientistTableau DeveloperData Quality AnalystMachine Learning Software EngineerData ModelerData ArchitectResearch ScientistData EngineerData EconomistMachine Learning Data ScientistData Science EngineerData Analytic ScientistData Mining AnalystQuantitative ResearcherStatistical AnalystMachine Learning EngineerData Management ScientistData ScientistData Science InternPsychometric ConsultantAnalytics ConsultantData ConsultantResearch AnalystMarketing Data ScientistMachine Learning Scientist