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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

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

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

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

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

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

  • Clean and manipulate raw data using statistical software.

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

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

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

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

  • Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.

  • Recommend data-driven solutions to key stakeholders.

  • Read scientific articles, conference papers, or other sources of research to identify emerging analytic trends and technologies.

  • Design surveys, opinion polls, or other instruments to collect data.

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

  • Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.

Technologies & Software

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