Data & AnalyticsTechnologyPlatinum

Determine if an action directly caused an outcome.

Causal Inference Analyst

Causal graphs, DiD, IV, RDD, synthetic controls

expertv5.0

Best for

▸Evaluate whether a marketing campaign actually caused sales lift vs correlation
▸Design A/B tests that account for network effects and interference between users
▸Estimate ROI of product feature launches using difference-in-differences analysis
▸Identify which customer acquisition channels truly drive retention vs just selection bias

What you'll get

▸DAG visualization with identified confounders and adjustment sets, plus DoWhy code implementing backdoor criterion estimation
▸Difference-in-differences analysis with parallel trends tests, event study plots, and heterogeneous treatment effect estimates by subgroup
▸Instrumental variables analysis with first-stage F-statistics, exclusion restriction validation, and LATE interpretation with confidence intervals

Expects

Clear causal question, observational or quasi-experimental data, and domain knowledge about potential confounders and data-generating process.

Returns

Causal effect estimates with confidence intervals, assumption validation tests, sensitivity analyses, and actionable recommendations with uncertainty quantification.

What's inside

“You are a Causal Inference Analyst. You bridge correlation and causation by rigorously identifying and estimating treatment effects from observational and quasi-experimental data. - Construct DAGs before selecting methods, ensuring identification strategy matches causal structure, not data shape - T...”

Covers

What You Do DifferentlyMethodologyWatch For

Not designed for ↓

×Pure machine learning prediction tasks without causal questions
×Basic correlation analysis or descriptive statistics
×Real-time recommendation systems or personalization engines
×Standard business intelligence dashboards or reporting

SupaScore

86.88▼

Research Quality (15%)

9.25

Prompt Engineering (25%)

8.75

Practical Utility (15%)

8.25

Completeness (10%)

User Satisfaction (20%)

8.5

Decision Usefulness (15%)

8.5

Evidence Policy

Standard: no explicit evidence policy.

causal-inferencedagdifference-in-differencesregression-discontinuityinstrumental-variablesdowhy

Research Foundation: 6 sources (2 books, 2 official docs, 2 paper)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.