AI for Data Scientists

AI you can use for this job

98 matched to the tools data scientists use. Showing 24.

• GitHub

  MCP server

  GitHub is the perfect place to share code and work collaboratively on private and open source software.

  GitHub

• PostgreSQL

  MCP server

  PostgreSQL is a powerful, open-source database engine with a uniquely advanced query optimizer and dozens of built in features, making it an easy choice for production databases.

  PostgreSQL

• GitHub

  App

  Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with GitHub MCP or direct API to manage repositories, review pull requests, track issues, and automate code workflows through natural language.

  Make (make.com)

• Snowflake

  MCP server

  Snowflake allows corporate users to store and analyze data using cloud-based hardware and software.

  Snowflake

• Snowflake

  App

  Equip your AI agents with Snowflake MCP or direct API to run SQL queries, schedule analytics jobs, monitor data quality, create secure shares, and manage warehouse resources through natural language.

  Make (make.com)

• Microsoft Power Bi

  App

  Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Microsoft Power Bi MCP or direct API to list workspaces, inspect reports, refresh datasets, and summarize dashboard insights through natural language.

  Make (make.com)

• Tableau

  App

  Tableau is a business intelligence and analytics platform that enables users to connect to databases, create data visualizations, and share insights. The platform offers deployment options including cloud-based, self-hosted, and desktop environments with drag-and-drop functionali

  Make (make.com)

• Tableau

  MCP server

• Amazon Redshift

  App

  Make (make.com)

• Amazon S3

  App

  Amazon S3 is a simple storage service that helps developers and IT teams store, backup, archive and retrieve data from anywhere across the web. It allows administrators to store data in buckets, append tags to objects, configure access controls for several clients, conduct high-v

• Atlassian Confluence

  MCP server

• Azure DevOps

  App

  Make (make.com)

• BigQuery

  App

  BigQuery is an autonomous data and AI platform that automates the entire data lifecycle from ingestion to insights. The platform features built-in predictive analytics, AI inferencing capabilities, and support for machine learning model training using SQL. It includes AI-powered

  Make (make.com)

• Elasticsearch

  App

  Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Elasticsearch MCP or direct API to search documents, manage indices, run analytics, and update records through natural language.

  Make (make.com)

• Google Cloud

  MCP server

• Jenkins

  App

  Make (make.com)

• Jenkins

  MCP server

  jenkins is a continuous integration server that monitors executions of repeated jobs, such as building a software project or jobs run by cron.

  Jenkins

• Looker

  MCP server

  Looker is an enterprise platform for BI, data applications, and embedded analytics that helps you explore and share insights in real time.

  Looker

• Looker

  App

  Looker is data analytics platform that makes it easy for everyone to find, explore and understand your business data.

• Microsoft Excel

  MCP server

  Microsoft's Excel is a spreadsheet application used by millions of users across the world. It is part of the Office ecosystem and is considered the industry standard for spreadsheets. Only files on OneDrive for Business (available with Office 365 and Sharepoint server) are su

  Microsoft Excel

• Microsoft Power BI

  MCP server

  Microsoft Power BI is a business analytics platform for visualizing data and sharing insights.

  Microsoft Power BI

• MongoDB

  App

  AI demands adaptability. MongoDB offers flexible, scalable, AI-ready data solutions, eliminating friction and accelerating innovation.

  Make (make.com)

• Mongodb

  MCP server

• Neo4j

  MCP server

  lobehub

The tools this job actually uses

87 documented for this occupation. Showing 40, hot technologies first. A filled dot means an AI solution exists for it.

• Alteryx softwarehot
• Amazon Elastic Compute Cloud EC2hot
• Amazon Redshifthot
• Amazon Web Services AWS softwarehot
• Apache Airflowhot
• Apache Cassandrahot
• Apache Hadoophot
• Apache Hivehot
• Apache Kafkahot
• Apache Sparkhot
• Atlassian Confluencehot
• Atlassian JIRAhot
• Bashhot
• Chot
• Chot
• Chot
• Dockerhot
• Elasticsearchhot
• Githot
• GitHubhot
• Gohot
• Google Looker Analyticshot
• IBM SPSS Statisticshot
• JavaScripthot
• JavaScript Object Notation JSONhot
• Jenkins CIhot
• Kuberneteshot
• Linuxhot
• Microsoft Accesshot
• Microsoft Azure softwarehot
• Microsoft Excelhot
• Microsoft Office softwarehot
• Microsoft Power BIhot
• Microsoft PowerPointhot
• Microsoft SQL Serverhot
• MongoDBhot
• NoSQLhot
• Oracle Javahot
• Perlhot
• PostgreSQLhot

What this job involves

16 documented tasks, most important first. Showing 16.

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