Senior Data Scientist

Senior Data Scientist

Durham or Burlington NC location Hybrid 3 days in office, 2 days remote

Day shift 8:00am-5:00pm

The Senior Data Scientist identifies opportunities through exploratory data analysis, develops and deploys machine learning models, and collaborates with diverse stakeholders to implement data-driven solutions

Job Responsibilities

• Produce innovative AI/ML solutions that drive business value across the Early Development Research areas of Labcorp
• Lead data science projects from requirements gathering through deployment with emphasis on Early Development area of organization
• Develop, validate, and implement machine learning models that solve real business problems
• Analyze complex datasets to identify patterns and opportunities for process improvement
• Translate technical concepts and findings into clear, actionable insights for non-technical audiences
• Balance business requirements with technical constraints to deliver optimal solutions
• Interpret and visualize data effectively for different audience levels
• Stay current with advancements in AI/ML and evaluate new technologies for potential applications
• Mentor junior team members and contribute to the AI team's knowledge base

• Master's degree in Big Data Analytics, Computer Science, Statistics, Mathematics OR Engineering
• 3 years or more experince working full time as a Data Engineer
• 5 years or more of experience with Python programming
• 3 years or more of leading technical projects
• 3 years or more of using AWS services

• 6 or more months working at Labcorp as a Data Scientist
• 2 years or more using AWS Services specific including Lambda, Glue, ECS, RDS, API Gateway, Bedrock, Step Functions, SQS, Athena, Sagemaker, Jenkins
• 2 years or more using Python Packages boto3, pandas, NumPy, TensorFlow/PyTorch, Matplotlib/Seaborn/Plotly, streamlite

• Broad knowledge of machine learning techniques including classification, regression, and deep learning approaches
• Deep expertise in at least one specialized ML area (e.g., reinforcement learning, optimization, Generative AI, computer vision, time series forecasting, predictive modeling)
• Ability to work with diverse data types including numerical, text, time series, and structured/unstructured data
• Strong problem-solving abilities and curiosity to navigate ambiguous business challenges
• Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders
• Proactive approach to identifying opportunities and solving problems
• Adaptability to work across various business domains and problem types
• Experience assessing tradeoffs in model development (e.g., accuracy vs. latency) based on business needs