Measurement Framework Developer - Data Scientist (Statistical & Causal Inference)

Ampcus, Inc; Pleasanton (CA); On-site; USD 90,000 - 130,000; Full time

Job summary

A global technology consulting firm in Pleasanton, CA is looking for a Measurement Framework Developer - Data Scientist. This role involves developing scalable frameworks for statistical and causal inference, applying various methodologies like A/B testing, and writing clean, reproducible code. Ideal candidates will have strong expertise in Python, SQL, and statistical libraries. Join a talented team focused on innovative enterprise solutions in a supportive environment.

Qualifications

• Strong expertise in statistical inference and causal analysis.
• Proficient in Python and SQL, with experience in relevant libraries.
• Self-starter with the ability to work independently.

Responsibilities

• Design and implement measurement frameworks for solutions in production.
• Apply statistical inference and causal methods.
• Develop and analyze controlled experiments and observational studies.

Skills

Statistical inference

Causal analysis

Hypothesis testing

Python

SQL

A/B testing

Tools

statsmodels

scikit-learn

DoWhy

Databricks

Job description

Measurement Framework Developer - Data Scientist (Statistical & Causal Inference)

Ampcus Inc. is a certified global provider of a broad range of Technology and Business consulting services. We are in search of a highly motivated candidate to join our talented Team.

Job Title: Measurement Framework Developer - Data Scientist (Statistical & Causal Inference)

Location(s): Pleasanton, CA.

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.

Preferred Qualifications

• Experience in retail, inventory management, or operations research.
• Exposure to cloud platforms (Azure, AWS, GCP).

Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.