Senior Data Scientist

What You'll Be Doing: Machine Learning & Predictive Analytics Design, build, deploy, and monitor machine learning models that support strategic business initiatives. Develop predictive solutions focused on customer behavior, campaign effectiveness, engagement, retention, and business performance. Perform feature engineering, model training, validation, tuning, and ongoing performance monitoring. Translate complex business challenges into scalable analytical solutions. Experimentation & Statistical Analysis Lead the design, execution, and interpretation of A/B tests and controlled experiments. Apply advanced statistical techniques to evaluate business and marketing initiatives. Develop measurement frameworks that quantify performance and identify optimization opportunities. Present actionable recommendations based on analytical findings. Marketing Analytics Partnership Serve as a key analytics partner to marketing leadership and cross-functional business teams. Support customer acquisition, retention, segmentation, personalization, and campaign measurement efforts. Deliver insights that influence marketing strategy and improve business outcomes. Communicate complex analytical concepts to both technical and non-technical audiences. Cloud Analytics & Data Engineering Work with large-scale datasets across multiple platforms and sources. Utilize Azure and Databricks environments to support analytics, machine learning, and model operationalization. Develop efficient data pipelines and analytical workflows using SQL and Python. Contribute to data quality, governance, and best-practice initiatives.

Required Qualifications: Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.7+ years of hands-on Data Science and Machine Learning experience. Experience working within the healthcare industry. Experience partnering directly with marketing organizations and stakeholders. Strong experience designing and analyzing A/B tests, experimentation frameworks, and statistical analyses. Advanced proficiency in Python for machine learning and analytics development. Advanced proficiency in SQL for querying and analyzing large-scale datasets. Demonstrated experience developing and deploying machine learning models including: Predictive Modeling Classification Regression Segmentation & Clustering Strong understanding of statistical methodologies, hypothesis testing, and experimental design. Ability to communicate technical findings and recommendations to executive and business stakeholders.

Preferred Qualifications: Experience with Microsoft Azure analytics and data services. Hands-on experience with Databricks for analytics, data engineering, or machine learning initiatives. Experience with Apache Spark and distributed data processing. Knowledge of MLOps and model lifecycle management.