Data Scientist

Candidates local in North Carolina will be preferred. Key Responsibilities • Lead the development and deployment of predictive and prescriptive models to optimize business outcomes across multiple domains. • Apply causal inference and statistical analysis techniques (e.g., propensity score matching, A/B testing, structural equation modeling, synthetic controls) to uncover cause–effect relationships and support decision-making. • Develop and operationalize NLP solutions for unstructured text data, including entity extraction, text classification, sentiment analysis, and topic modeling. • Build, optimize, and maintain large-scale data pipelines and analytical workflows in Azure and Databricks environments. • Collaborate with cross-functional teams (engineering, product, business stakeholders) to translate business problems into data science solutions. • Communicate insights and recommendations clearly through visualizations, reports, and presentations to technical and non-technical audiences. • Contribute to building best practices in model development, deployment, and monitoring. Required Qualifications • 5+ years of professional experience in Data Science or Advanced Analytics. • Strong expertise in predictive modeling, prescriptive analytics, and statistical methods (regression, classification, clustering, optimization). • Hands-on experience with causal analysis (e.g., causal inference frameworks, experiments, quasi-experiments). • Proficiency in Natural Language Processing (NLP) using modern libraries (e.g., HuggingFace, Spark NLP, spaCy). • Proficient in Python (pandas, scikit-learn, statsmodels, PySpark) and SQL. • Advanced knowledge of Databricks for large-scale data engineering and machine learning workflows. • Strong experience with Azure Cloud Services (e.g., Azure Machine Learning, Azure Data Lake, Fabric, Azure SQL, Functions). • Solid understanding of MLOps practices (versioning, CI/CD for ML, monitoring, reproducibility). • Excellent communication skills with ability to present findings to both technical and executive stakeholders. Preferred Qualifications • Advanced degree (MS or PhD) in Data Science, Computer Science, Statistics, Applied Mathematics, or related field. • Experience with deep learning frameworks (TensorFlow, PyTorch) for NLP and other advanced modeling tasks. • Exposure to healthcare, life sciences, or other regulated industries where causal analysis and interpretability are critical. • Familiarity with reinforcement learning, prescriptive optimization, or advanced decision sciences. • Contributions to open-source projects, publications, or thought leadership in the data science community.