Measurement Framework Developer

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)