Browse Skills

Expert guidance on real-time stream processing architectures using Apache Kafka, Flink, and Spark Streaming, covering windowing strategies, exactly-once semantics, CEP, and operational best practices.

Maps end-to-end data lineage from source systems through transformations to downstream consumers, enabling impact analysis, debugging data quality issues, and ensuring regulatory compliance.

Designs and implements Monte Carlo simulations for quantitative analysis, covering probability distributions, variance reduction techniques, financial modeling (VaR, options pricing), convergence analysis, sensitivity analysis, and production-quality Python/R implementation patterns.

Designs unified customer profiles using Segment, RudderStack, or custom CDP solutions with identity resolution, event streaming, audience segmentation, and privacy-compliant data governance.

Designs normalized event tracking schemas for product analytics, defining event taxonomies, property standards, and validation rules to ensure consistent data collection across teams.

Builds and evaluates demand forecasting systems using statistical time series methods and machine learning, covering decomposition, model selection, accuracy measurement, and translation to inventory and planning decisions.

Designs and implements time series forecasting solutions — from data preprocessing and stationarity testing through model selection (ARIMA, Prophet, LSTM, Transformer-based), evaluation with proper temporal cross-validation (MAPE, RMSE, MASE), to production deployment with ensemble approaches and drift monitoring.

Designs dimensional data warehouse schemas using Kimball, Inmon, or Data Vault methodologies. Guides star/snowflake schema design, slowly changing dimensions, ETL/ELT patterns, and cloud warehouse optimization for Snowflake, BigQuery, and Redshift.

Guides analytics engineering best practices using dbt, SQL modeling patterns, semantic layers, metrics definitions, and testing strategies. Helps design maintainable, well-documented analytics workflows from raw data to business-ready datasets.

Designs real-time analytics systems using stream processing frameworks like Kafka Streams, Apache Flink, and Spark Streaming. Covers event-time processing, windowing strategies, exactly-once semantics, and low-latency dashboard architectures.

Guides you through designing effective, insight-driven dashboards with proper KPI selection, visual encoding, and data storytelling — applying Tufte and Few principles to avoid common anti-patterns.

Guides you through building robust data quality frameworks — from validation rules and schema enforcement to data observability, data contracts, and remediation workflows — using industry tools like Great Expectations and Soda.

Designs and executes rigorous causal evaluations of policy interventions using econometric methods like DiD, RDD, and instrumental variables, with OECD and EU regulatory frameworks.

Prepare research outputs for public sharing and long-term preservation with FAIR-compliant data packaging, reproducible environments, proper licensing, and repository publication strategies.

Expert analytics engineering skill for dbt Core/Cloud — guides you through SQL-based data modeling with staging/intermediate/mart layers, dimensional modeling (Kimball methodology), incremental models, SCD Type 2 snapshots, comprehensive testing strategies, Jinja macros, dbt packages, and warehouse-specific optimization for Snowflake, BigQuery, and Redshift.

Guide systematic exploratory data analysis workflows — from initial profiling through distribution analysis, correlation discovery, and hypothesis generation — using statistical rigor and effective visualization.

Guide practitioners through selecting, designing, and interpreting statistical hypothesis tests with proper assumptions checking, sample size calculations, and actionable conclusions.

Design, analyze, and interpret A/B tests using Bayesian statistical methods. Provides posterior distributions, credible intervals, expected loss calculations, and actionable recommendations for experiment-driven decision making.

Design and calibrate risk scoring systems that identify at-risk individuals within cohorts — enabling early interventions for student retention, customer churn prevention, patient readmission, and other predictive analytics use cases.

Designs measurable outcome indicator frameworks for social impact programs, including theories of change, logic models, SMART indicators, and results-based monitoring systems.

Designs retention measurement systems, builds churn prediction models, and creates data-driven intervention strategies that measurably reduce customer churn across SaaS, e-commerce, and subscription businesses.

Rigorous causal inference methods for isolating the true impact of price changes on demand, revenue, and customer behavior using econometric techniques, DAG-based reasoning, and experimentation design.

Design, optimize, and operate ClickHouse OLAP clusters for real-time analytics on billions of rows with sub-second query performance.

Design and build custom, interactive data visualizations using D3.js with proper data binding, responsive layouts, accessible markup, and publication-quality visual encoding.