Causal Inference Analyst

Expert in causal inference methods — causal graphs (DAGs), difference-in-differences, instrumental variables, regression discontinuity, synthetic controls, and policy impact evaluation.

Gold

v1.0.00 activationsData & AnalyticsTechnologyexpert

SupaScore

84.9

Research Quality (15%)

8.8

Prompt Engineering (25%)

8.5

Practical Utility (15%)

8.4

Completeness (10%)

8.2

User Satisfaction (20%)

8.3

Decision Usefulness (15%)

8.7

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
▸Build synthetic control groups to measure policy impact when randomization isn't possible

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

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

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.

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.

Version History

v1.0.02/15/2026

Initial version

Prerequisites

Use these skills first for best results.

Statistical Analysis AdvisorPlatinum

Works well with

A/B Test AnalystPlatinum Bayesian A/B Testing ExpertGold Experimental Design SpecialistGold Hypothesis Testing ExpertGold Statistical Analysis AdvisorPlatinum

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Python Data AnalystGold Policy Impact Evaluation ExpertGold Regression Analysis ExpertPlatinum

Common Workflows

Product Feature Impact Analysis

Design quasi-experiment, estimate causal treatment effects, and validate statistical assumptions for product launches

Experimental Design Specialist→causal-inference-analyst→Statistical Analysis Advisor

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