Data Scientist

Summary / Quick Intro We are seeking a Data Scientist with strong expertise in statistical inference and causal analysis to design and build measurement frameworks for enterprise solutions. This role focuses on designing experiments, applying causal inference techniques, and developing scalable systems to measure business impact. The ideal candidate will combine strong analytical thinking with practical engineering skills to deliver reliable insights and data-driven decision frameworks. Pay range :$55 /hr to $60/hr on w2 • Responsibilities • Design and implement measurement frameworks for solutions deployed in production environments • Apply statistical inference and causal methods such as A/B testing, propensity score matching, and instrumental variables • Develop and analyze controlled experiments and observational studies to measure product or operational impact • Collaborate with business and technical stakeholders to define KPIs, success metrics, and measurement strategies • Write clean, reproducible code for statistical analysis, experimentation, and reporting • Implement CI/CD practices and maintain code repositories using GitHub Enterprise • Work within enterprise data environments such as Databricks to manage large-scale datasets and analysis pipelines • Qualifications • Strong understanding of hypothesis testing, OLS, GLM, and causal inference techniques • Proficiency in Python and SQL for statistical modeling and data analysis • Experience with libraries such as statsmodels, scikit-learn, DoWhy, and linearmodels • Hands-on experience with A/B testing and experimental design methodologies • Familiarity with enterprise cloud analytics environments such as Databricks • Strong problem-solving ability with a self-starter mindset and ownership mentality • Ability to work independently while collaborating effectively with cross-functional teams Preferred Qualifications • Experience in retail, inventory management, or operations research domains • Exposure to cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform • Call to Action If you are passionate about causal inference, experimentation, and building data-driven measurement frameworks, apply today and help shape the future of enterprise analytics. Summary / Quick Intro We are seeking a Data Scientist with strong expertise in statistical inference and causal analysis to design and build measurement frameworks for enterprise solutions. This role focuses on designing experiments, applying causal inference techniques, and developing scalable systems to measure business impact. The ideal candidate will combine strong analytical thinking with practical engineering skills to deliver reliable insights and data-driven decision frameworks. • Responsibilities • Design and implement measurement frameworks for solutions deployed in production environments • Apply statistical inference and causal methods such as A/B testing, propensity score matching, and instrumental variables • Develop and analyze controlled experiments and observational studies to measure product or operational impact • Collaborate with business and technical stakeholders to define KPIs, success metrics, and measurement strategies • Write clean, reproducible code for statistical analysis, experimentation, and reporting • Implement CI/CD practices and maintain code repositories using GitHub Enterprise • Work within enterprise data environments such as Databricks to manage large-scale datasets and analysis pipelines • Qualifications • Strong understanding of hypothesis testing, OLS, GLM, and causal inference techniques • Proficiency in Python and SQL for statistical modeling and data analysis • Experience with libraries such as statsmodels, scikit-learn, DoWhy, and linearmodels • Hands-on experience with A/B testing and experimental design methodologies • Familiarity with enterprise cloud analytics environments such as Databricks • Strong problem-solving ability with a self-starter mindset and ownership mentality • Ability to work independently while collaborating effectively with cross-functional teams Preferred Qualifications • Experience in retail, inventory management, or operations research domains • Exposure to cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform • Call to Action If you are passionate about causal inference, experimentation, and building data-driven measurement frameworks, apply today and help shape the future of enterprise analytics.