Title: Measurement Framework Developer
Location: Remote
Duration: 6-12 months project
Interview process: 2 video interviews
Visa: USC, GC, F1, H4
Retail industry required
Must have LinkedIn
Please ensure that the candidate profiles are qualified.
Measurement Framework (fyi this creates a hierarchy that connects operations to strategy--- think KPI's / Metrics/ Dimensions
Retail industry required
Candidates must have experience designing experiments, applying causal inference methods, and building scalable frameworks to measure impact.
Strong knowledge of hypothesis testing, OLS, GLM, and causal inference techniques.
Proficiency in Python and SQL; experience with libraries like stats models, scikit-learn, DoWhy, linear models.
Experience with A/B testing and experimental design.
Familiarity with Databricks or similar enterprise cloud environments (AWS/ Azure, GCP) .
FYI
Developing a framework is a coding or technical implementation process
Defining the data model (translate business requirements to specific data points and naming conventions for consistency)
Creating a data dictionary (define the metrics / calculation/ source - documentation)
Implementing tagging/ tracking (setting up analytics tools to capture
About the Role
We are looking for a Data Scientist with strong expertise in statistical inference and causal analysis to develop measurement frameworks for enterprise solutions. This role is ideal for someone passionate about designing experiments, applying causal inference methods, and building scalable frameworks to measure impact.
Key Responsibilities
Design and implement measurement frameworks for solutions in production.
Apply statistical inference and causal methods (e.g., A/B testing, propensity score matching, instrumental variables).
Develop and analyze controlled experiments and observational studies.
Collaborate with stakeholders to define KPIs and measurement strategies.
Write clean, reproducible code for statistical analysis and reporting.
Implement CI/CD principles and manage code repositories using GitHub Enterprise.
Required Qualifications
Strong knowledge of hypothesis testing, OLS, GLM, and causal inference techniques.
Proficiency in Python and SQL; experience with libraries like statsmodels, scikit-learn, DoWhy, linearmodels.
Experience with A/B testing and experimental design.
Familiarity with Databricks or similar enterprise cloud environments.
Self-starter with an ownership mindset and ability to work independently.
Qualifications
Experience in retail, inventory management, or operations research.
Exposure to cloud platforms (Azure, AWS, GCP).
Measurement Framework (fyi this crates a hierarchy that connects operations to strategy--- think KPI's / Metrics/ Dimensions
Retail
designing experiments, applying causal inference methods, and building scalable frameworks to measure impact.
Strong knowledge of hypothesis testing, OLS, GLM, and causal inference techniques.
Proficiency in Python and SQL; experience with libraries like statsmodels, scikit-learn, DoWhy, linearmodels.
Experience with A/B testing and experimental design.
Familiarity with Databricks or similar enterprise cloud environments (AWS/ Azure, GCP) .
FYI
Developing a framework is a coding or technical implementation process
Defining the data model (translate business requirements to specific data points and naming conventions for consistency)
Creating a data dictionary (define the metrics / calculation/ source - documentation)
Implementing tagging/ tracking (setting up analytics tools to capture specific events and user properties : conversion funnel steps)