Sr Data Scientist

• Leverage expertise in handling large, complex datasets to perform exploratory data analysis, feature engineering, and statistically sound sample design
• Build, validate, deploy, and enhance complex predictive and machine learning models using data from multiple structured and unstructured sources to materially improve business outcomes
• Design, build, deploy, and monitor machine learning models in production environments, ensuring scalability, reliability, and performance
• Implement model lifecycle management best practices including versioning, experiment tracking, monitoring, retraining strategies, and performance optimization (e.g., MLflow or similar frameworks)
• Automate feedback loops for algorithms and models in production while creating scalable, repeatable data science processes and production-grade data products
• Design and execute experiments (A/B testing, causal inference frameworks) to evaluate model performance and business impact
• Act as a technical subject matter expert, recommending and developing innovative analytical approaches aligned with strategic priorities
• Translate complex analytical findings into clear business insights and present results to executive and non-technical audiences
• Mentor junior data scientists and contribute to establishing enterprise best practices in modeling, governance, and documentation
• Collaborate with data engineering teams to ensure robust pipelines, high data quality, and scalable model deployment
• Influence cross-functional teams and drive adoption of data-driven decision-making
• Other duties as assigned

• Bachelor’s degree or equivalent experience in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, or related discipline
• Master’s or PhD preferred
• 5–7+ years of professional experience building, validating, deploying, and monitoring predictive and machine learning models in production environments
• Strong programming expertise in Python with hands-on experience building end-to-end ML solutions
• Experience with MLflow (or similar model lifecycle tools) for experiment tracking, model versioning, and deployment management
• Experience working with SQL and large-scale data processing frameworks such as Apache Spark
• Experience designing scalable data solutions in modern data platforms
• experience with Microsoft Fabric is a plus
• Proven experience applying machine learning techniques (e.g., regression, classification, clustering, ensemble methods, NLP, etc.)
• Strong communication skills with the ability to explain complex analytical concepts to non-technical stakeholders

Experience with Microsoft Fabric is a plus

• medical
• dental
• vision
• 401k
• PTO/paid sick leave
• employee stock purchase plan