Causal Inference Jobs in Tennessee (NOW HIRING)

Biostatistics methods will include complex survival analysis, longitudinal analysis, machine learning, and causal inference. You will benefit from access to unique datasets and expertise from two of ...

Econometric Analysis / Causal Inference * Create matched samples of schools and students (e.g., propensity score matching, exact/coarsened exact matching, weighting). * Implement quasi-experimental ...

Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM; survival analysis; random forest) * Trial emulation frameworks * External control arm development and ...

... causal inference and translating results into business actions • Demonstrated ability to mentor others and influence cross-functional partners toward adoption Company : Starbucks is a restaurant ...

... clustering, causal inference) • Experience with data visualization tools (e.g., Tableau, Power BI, or similar) • Strong communication skills and attention to detail Preferred : • Degree ...

... in causal inference, risk stratification, and precision medicine • Experience in transforming complex clinical/biological data into meaningful representations (including advanced feature ...

... classification, causal inference, clustering) • Experience with cloud data/analytics solutions (e.g., Azure or AWS) • Experience managing and coaching a team, with strong written/verbal ...

Strong analytics foundation, with experience in areas such as causal inference, advanced statistical modeling, and machine learning as they apply to marketing effectiveness. * Delivery Management:

All areas of biostatistics are of interest; we are especially interested in candidates with a demonstrated interest in artificial intelligence, high-dimensional data, and causal inference. We are ...

All areas of biostatistics are of interest; we are especially interested in candidates with a demonstrated interest in artificial intelligence, high-dimensional data, and causal inference. We are ...

Demonstrated expertise in advanced quantitative methods, such as longitudinal data analysis, hierarchical linear modeling, causal inference, or the analysis of large-scale administrative and survey ...

Knowledge of uncertainty quantification methods and causal inference for complex environmental systems. * Experience with large-scale Earth system simulations, particularly using the Energy Exascale ...

Knowledge of uncertainty quantification methods and causal inference for complex environmental systems. * Experience with large-scale Earth system simulations, particularly using the Energy Exascale ...

Demonstrated experience with causal inference methods. * Experience working with large datasets and writing clean, well-documented code. Knowledge, Skills, Abilities: * Advanced programming skills in ...

Demonstrated expertise in advanced quantitative methods, such as longitudinal data analysis, hierarchical linear modeling, causal inference, or the analysis of large-scale administrative and survey ...

Experience applying statistical methods, hypothesis testing, experimental design, causal inference, and model evaluation techniques to support data-driven decision making. * Experience working with ...

Apply advanced analytical methods such as machine learning, forecasting, optimization, causal inference, and experimentation to solve high-value business problems. * Proactively identify trends and ...

Experience applying statistical methods, hypothesis testing, experimental design, causal inference, and model evaluation techniques to support data-driven decision making. * Experience working with ...

Working knowledge of common modeling techniques (e.g., regression, classification, decision trees, clustering, causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI ...

Familiarity with experiment design / causal inference and translating results into business actions * Demonstrated ability to mentor others and influence cross-functional partners toward adoption As ...