Browse Skills

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.

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

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

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

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.

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.

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.

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

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

Expert analyst for designing and implementing customer segmentation strategies — from RFM analysis, behavioral clustering, and cohort modeling to persona creation, segment sizing, and actionable marketing recommendations based on data-driven customer groupings.

Create publication-quality static figures with Matplotlib and interactive web-ready visualizations with Plotly, guided by visual perception research and data storytelling principles.

Design domain-oriented, decentralized data architectures using data mesh principles including data-as-a-product, self-serve infrastructure, and federated computational governance.

Designs and implements enterprise skills taxonomies and competency frameworks that enable skills-based workforce planning, internal mobility, gap analysis, and learning path mapping using validated I/O psychology methodologies.

Expert guidance for building and optimizing Apache Spark data processing pipelines, from PySpark development to cluster tuning and lakehouse architecture.

Expert in MongoDB production systems — document modeling, aggregation pipelines, sharding, indexing strategy, Atlas operations, and migration from relational databases.

Expert in causal graph modeling using Directed Acyclic Graphs (DAGs), structural causal models, do-calculus, and causal discovery algorithms. Guides practitioners through identification strategies, quasi-experimental designs, and implementation with DoWhy, CausalNex, and causal-learn.

Guides teams through MongoDB Atlas production deployments — cluster architecture, performance optimization, Atlas Search, security hardening, backup strategies, and cost management for cloud-native document database workloads.

Design and implement cohort analyses for retention measurement, behavioral segmentation, and product analytics. Provides SQL implementations, visualization recommendations, and statistical interpretation guidance.

Designs and implements sophisticated Airtable automations, scripting extensions, and integration workflows that transform manual business processes into reliable, scalable automated systems.

Expert in Google BigQuery — SQL analytics at scale, partitioning and clustering strategies, BigQuery ML, materialized views, Dataform pipelines, cost optimization, and data governance.

Design data activation pipelines that sync analytical data from cloud data warehouses back into operational SaaS tools like CRMs, marketing platforms, and support systems.

Build, evaluate, and deploy machine learning models directly in Google BigQuery using SQL, from classification and regression to time-series forecasting and recommendations.