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Data

Connect APIs, databases, warehouses, spreadsheets, analytics, and ETL workflows.

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How to use this page

What team job or business role does the user need filled?

Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.

Common Job Briefs

Start from user language

  • Connect a dataset or API to a reusable analysis workflow.
  • Evaluate extraction, transformation, and retrieval candidates.
Playbooks and teams

Sandbox-first next steps

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Data candidates

Showing 12 of 4771. Adjust filters to narrow the review list without losing job context.

Open family guide
Coding & Development

Operational patterns for LLM inference: latency budgeting, tail-latency control, caching, batching/scheduling, quantization/compression, parallelism, and reliable serving at scale. Emphasizes production-grade performance, cost control, and observability.

playbooks skill MCP, HTTP, CLI Needs review
Fit61 / 100
TrustNeeds review
InstallMCP ready
DecisionNeeds review
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Coding & Development

End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (...

playbooks skill MCP, HTTP, CLI Needs review
Fit61 / 100
TrustNeeds review
InstallMCP ready
DecisionNeeds review
Review links
Coding & Development

Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptiv...

playbooks skill MCP, HTTP, CLI Needs review
Fit61 / 100
TrustNeeds review
InstallMCP ready
DecisionNeeds review
Review links
Coding & Development

Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).

playbooks skill MCP, HTTP, CLI Needs review
Fit61 / 100
TrustNeeds review
InstallMCP ready
DecisionNeeds review
Review links
Coding & Development

Operational prompt engineering for production LLM apps: structured outputs (JSON/schema), deterministic extractors, RAG grounding/citations, tool/agent workflows, prompt safety (injection/exfiltration), and prompt evaluation/regression testing. Use when designing, debugging, or standardizing prompts for Codex CLI, Claude Code, and OpenAI/Anthropic/Gemini AP...

playbooks skill MCP, HTTP, CLI Needs review
Fit61 / 100
TrustNeeds review
InstallMCP ready
DecisionNeeds review
Review links
Coding & Development

Complete RAG and search engineering skill. Covers chunking strategies, hybrid retrieval (BM25 + vector), cross-encoder reranking, query rewriting, ranking pipelines, nDCG/MRR evaluation, and production search systems. Modern patterns for retrieval-augmented generation and semantic search.

playbooks skill MCP, HTTP, CLI Needs review
Fit61 / 100
TrustNeeds review
InstallMCP ready
DecisionNeeds review
Review links
Coding & Development

Guide for designing effective tools for AI agents. Use when creating tools for custom agent systems or any AI tool interfaces. Provides principles for tool naming, input/output design, error handling, and evaluation methodologies that maximize agent effectiveness.

playbooks skill MCP, HTTP, CLI Needs review
Fit61 / 100
TrustNeeds review
InstallMCP ready
DecisionNeeds review
Review links
Review support

Review links

Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.

Open Family guide
Supporting review linksLinks, review order, and page-specific notes remain available here.

4771 candidates for Data. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.

Role-family review path
  1. 01Site contextShared review rules
  2. 02Role familyOpen the focused review record
  3. 03Profile pageOpen the candidate page
  4. 04Profile resourcesEvidence, setup, trust, trial, and history files

Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.

Review route: OpenAI review tools can start with openai.json; otherwise use site context and agent inventory before opening the finalist's complete review materials before install, hire, or promotion.