Senior Data Scientist

Labcorp•Durham, NC

9d•Hybrid

About The Position

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.

Requirements

Master's degree in Big Data Analytics, Computer Science, Statistics, Mathematics OR Engineering
3 years or more experience 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

Nice To Haves

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

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