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Automation Risk Analysis

Will “Marketing Data Scientist” be Automated?

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AI Exposure Risk

43%

“Marketing Data Scientist” will probably not be replaced by AI.

Based on the cognitive demands, communication requirements, and logical reasoning intrinsic to this occupation according to O*NET data, we project a 43% probability of disruption by generative AI and Large Language Models.

Automation & Robot Risk

1%

“Marketing Data Scientist” will not be replaced by robots.

Evaluating the physical dexterity, repetitive motion tasks, and manual labor associated with this role, our analysis indicates a 1% likelihood of substitution by advanced robotics systems.

Personal & Financial Insights

Every occupation has a unique profile. For Data Scientists, the Bureau of Labor Statistics and O*NET classify the day-to-day work broadly as: 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.

Avg. Annual Salary $124,590
Avg. Hourly Wage $59.90
Available Jobs (US) 233,440
Job Title & Hierarchy Code (SOC) Data Scientists #15-2051
Wage vs. National Median
ℹ️

Data is based on the reference occupation: “Data Scientists”

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Core Skills & Abilities

  • Identify relationships and trends or any factors that could affect the results of research.

  • Write new functions or applications in programming languages to conduct analyses.

  • 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.

  • Clean and manipulate raw data using statistical software.

  • Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.

  • Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.

  • Analyze, manipulate, or process large sets of data using statistical software.

  • Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.

  • 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.

  • Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.

  • Recommend data-driven solutions to key stakeholders.

  • Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.

  • Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.

  • Identify business problems or management objectives that can be addressed through data analysis.

Technologies & Software

  • Shiny
  • Python
  • Amazon Simple Storage Service S3
  • v0 by Vercel
  • Microsoft Access
  • spaCy
  • Geographic information system GIS systems
  • R
  • Apache Pig
  • Reporting software
  • MapReduce big data software
  • GitHub
  • NoSQL
  • JavaScript Object Notation JSON
  • Atlassian JIRA
  • OpenAI ChatGPT
  • C++
  • Neo4j
  • Scala
  • C
  • UNIX
  • Kubernetes
  • Elasticsearch
  • Amazon Web Services AWS software
  • MongoDB
  • Microsoft Power BI
  • Snowflake
  • StataCorp Stata
  • Linux
  • PostgreSQL
  • Claude (Anthropic)
  • Keras
  • Business intelligence software
  • pandas
  • Management information systems MIS
  • Microsoft SQL Server
  • Microsoft Azure software
  • JavaScript
  • Amazon CodeWhisperer
  • Git
  • Lovable.dev
  • Amazon Web Services AWS SageMaker
  • Mistral AI (chat/models)
  • Gemini Code Assist
  • Cursor AI
  • Microsoft Office software
  • Mlflow
  • Tabnine
  • Ruby
  • PyTorch
  • Mathematical software
  • Amazon Redshift
  • Shell script
  • Apache Kafka
  • Perl
  • Statistical software
  • Codeium
  • Flask
  • Splunk Enterprise
  • Amazon Elastic Compute Cloud EC2
  • Google Looker Analytics
  • Bolt.new
  • BigQuery
  • Apache Hive
  • Jenkins CI
  • Jupyter software
  • Julia
  • TensorFlow
  • Apache Cassandra
  • Apache Airflow
  • Structured query language SQL
  • Microsoft PowerPoint
  • Microsoft Excel
  • The MathWorks MATLAB
  • Google Antigravity
  • C#
  • PySpark
  • Apache MXNet
  • NumPy
  • XGBoost
  • SciPy
  • Oracle Java
  • GitHub Copilot
  • Kubeflow
  • Google Cloud software
  • RESTful API
  • Go
  • Perplexity AI
  • Bash
  • Apache Hadoop
  • Scikit-learn
  • Devin (Cognition AI)
  • Alteryx software
  • Apache Spark
  • Atlassian Confluence
  • IBM SPSS Statistics
  • Qlik Tech QlikView
  • Teradata Database
  • Tableau
  • Docker
  • SAS