Lead Data Scientist Position Available In Wake, North Carolina

As a Lead Data Scientist , you will be responsible for the ideation, development, maintenance, scaling, and support of AI/ML and advanced analytical models with an initial focus on pricing and commercial applications. This role requires advanced analytical skills, a strong foundation in statistical modeling and machine learning, and the ability to translate business problems into scalable data science solutions. The ideal candidate should have at least 7 years of experience in similar roles, strong Python skills, and a proven track record of operationalizing models that deliver business value. This position is based full-time, on-site in Raleigh, NC. Local candidates preferred.

Responsibilities:

Collaborate with Finance, Business and other cross-functional stakeholders, leading data science initiatives from design through deployment, ensuring solutions align with business objectives Analyze requirements and architect appropriate recommendations for AI/ML models Incorporate or integrate AI/ML solutions with current BI tools Conduct exploration, data extraction, cleansing and standardizing, classification, consumption, and data wrangling to identify trends or correlations in the company’s data Maintain data pipelines, ensure high data integrity, and monitor/iterate on deployed models to ensure long-term performance and reliability Maintain and enhance tree-based models in production, including CHAID, CART, Random Forest, and Gradient Boosting Clearly explain complex analytics, model choices, and trade-offs to non-technical stakeholders to build trust and drive adoption Ability to work with managers and stakeholders to identify and measure success criteria for predictive or prescriptive analytics solutions Collaborate with full-stack engineering teams to expose models via API or Python libraries Solid understanding of CI/CD, testing frameworks, and version control (Git) Foster team development through pair programming, code reviews, and regular knowledge-sharing sessions Perform all activities in accordance with the Company’s Mission, Vision, and Values, and in compliance with the Company’s policies, procedures, and

Code of Ethical Business Conduct Qualifications:

Bachelor of Science degree in Computer Science, Mathematics, Statistics, Data Science, or other quantitative fields Expert proficiency in Python and libraries such as pandas, NumPy, scikit-learn, TensorFlow, and/or PyTorch with 5+ years of applied data science experience Thorough understanding of classification, probability, regression, statistics, and machine learning models Experience with commercial or pricing models Proven experience in statistical modeling techniques and data structures Proficiency with AWS-based model deployment workflows Familiar with AWS data and ML services including S3, Lambda, Batch, SageMaker, and Step Functions Experience with data visualization tools such as

Matplotlib, Seaborn, Plotly, or Tableau Key Competencies:

Analytical thinking and problem solving; ability to interpret complex data and develop actionable solutions Technical rigor

• Keen attention to performance, accuracy, and scalability in production systems Communication
• Strong communication (written and verbal) and presentation skills Collaboration
• Comfortable working across teams in a dynamic, fast-paced environment Ethics and professionalism
• High integrity, discretion, and adherence to corporate values and standards #LI-JN2