Data & Analytics

Product analytics rules: calendar spine cross-joins, date boundary caps, event type pivoting, first-run NULL behavior.

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 (monitoring and retraining).

Master high-performance rendering for large datasets with Datashader. Use this skill when working with datasets exceeding 100M+ points, optimizing visualization performance, or implementing efficient rendering strategies with rasterization and colormapping techniques.

When the user wants to identify and mitigate supply chain risks, build resilience, or develop business continuity plans. Also use when the user mentions "supply chain risk," "disruption management," "resilience," "risk assessment," "business continuity," "scenario planning," "supply chain vulnerability," "risk modeling," or "crisis management." For supplier-specific risks, see supplier-risk-management. For compliance risks, see compliance-management.

Comprehensive personal finance management system for analyzing transaction data, generating insights, creating visualizations, and providing actionable financial recommendations. Use when users need to analyze spending patterns, track budgets, visualize financial data, extract transactions from PDFs, calculate savings rates, identify spending trends, generate financial reports, or receive personalized budget recommendations. Triggers include requests like "analyze my finances", "track my spen...

Data-driven business analysis with modern analytics, BI tools, and strategic insights. Use when analyzing business data, creating dashboards, running experiments, or generating data-driven recommendations.

Complete well log evaluation workflow from LAS/DLIS loading through QC, petrophysical analysis, lithology classification, and visualization. Use when performing formation evaluation from well log data.

Use when establishing measurement programs, analyzing metrics with statistical process control, setting baselines, or implementing CMMI Level 4 quantitative management - prevents vanity metrics and measurement theater

Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

Expert in quantitative finance, algorithmic trading, and financial data analysis using Python (Pandas/NumPy), statistical modeling, and machine learning.

Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.

When the user wants decision support systems, recommendation engines, or prescriptive analytics. Also use when the user mentions "decision optimization," "recommendation system," "what should we do," "action recommendations," "decision support," "intelligent recommendations," "automated decisions," or "prescriptive models." For pure optimization, see optimization-modeling. For forecasting, see demand-forecasting.

Multi-project portfolio analytics dashboard. Aggregate KPIs across projects, track portfolio health, compare performance, and support executive decision-making.

Compare results across multiple OrcaFlex simulations for design verification,

Post-process OrcaFlex simulation results using OPP (OrcaFlex Post-Process).

Perform operability analysis combining multiple sea states to assess

Extract extreme response values with linked statistics from OrcaFlex

Analyze multi-contract correlations for forecast-based hedge recommendations. Use when managing correlated assets. Trigger with 'analyze correlations' or 'suggest hedge'.

Analyze multi-contract correlations for forecast-based hedge recommendations. Use when managing correlated assets. Trigger with 'analyze correlations' or 'suggest hedge'.

Compute well-defined metrics from existing formulas, datasets, or test outputs. Use as an explicit/manual helper when the metric definition is already known, not for choosing the overall analysis owner or dashboard strategy.

Analyze construction labor productivity using data analytics. Track worker performance, identify inefficiencies, predict resource needs, and optimize crew allocation for maximum efficiency.

Comprehensive personal finance management system for analyzing transaction data, generating insights, creating visualizations, and providing actionable financial recommendations. Use when users need to analyze spending patterns, track budgets, visualize financial data, extract transactions from PDFs, calculate savings rates, identify spending trends, generate financial reports, or receive personalized budget recommendations. Triggers include requests like "analyze my finances", "track my spen...

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scien...

Analyze datasets to answer defined questions through statistical methods, trend identification, hypothesis testing, and correlation analysis. Use when the user needs evidence-backed findings or decisions from data; use exploratory-data-analysis instead for open-ended first-pass profiling before questions are defined.