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Senior Data Scientist
Senior Data ScientistLabCorp • Raleigh NC
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Senior Data Scientist

Senior Data Scientist

LabCorp • Raleigh NC
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Labcorp is hiring a Senior Data Scientist. This person will produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Apply knowledge of statistics, data modeling, data science, artificial intelligence, software engineering / architecture to recognize patterns, identify opportunities and make valuable discoveries. Use a flexible, analytical approach to design, develop, deploy, and evaluate predictive models. Generate and test hypotheses.

Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets, with an expanded focus on Generative AI applications. Apply knowledge of statistics, data modeling, data sciences, and artificial intelligence to recognize patterns, identify opportunities, and make valuable discoveries. Use a flexible, analytical approach to design, develop, and evaluate both traditional predictive models and generative AI systems. Generate and test hypotheses across various modeling paradigms.

Applicants who live within 35 miles of either the Burlington, NC or Durham, NC location will follow a hybrid schedule. This schedule includes a minimum of three in office days per week at an assigned location, either Burlington or Durham, supporting both collaboration and flexibility.

RESPONSIBILITIES

  • Interpret data and present insights through rich and intuitive visualizations that tell compelling stories.
  • Develop novel ways of integrating, mining, and visualizing diverse, high-dimensional, and poorly curated data sets.
  • Explore and implement generative AI techniques where appropriate to enhance data analysis capabilities and create new solutions.
  • Develop and deliver presentations to communicate technical ideas and analytical findings to non-technical partners and senior leadership.
  • Build underlying software infrastructure to better manage, integrate, and mine data, incorporating both traditional and generative AI approaches.
  • Work closely with engineering teams and participate in the full development cycle from product inception and research to production deployment.
  • Write production quality code while implementing both established methods and innovative AI solutions.

REQUIREMENTS

Knowledge, Skills & Abilities :

  • Experience in artificial intelligence and statistical learning.
  • Experience with statistical methodologies and machine learning techniques such as : neural networks, graphical models, ensemble methods and natural language processing.
  • Experience with multiple deep learning techniques such as CNN, LSTM, RNN, etc., in addition to standard machine learning approaches such as those found in scikit-learn.
  • Master of evaluation techniques for supervised and unsupervised techniques. Knows to evaluate the quality of data and determine gaps in data or assumptions.
  • Proficiency with Python. Can develop meaningful python code using objective oriented programming and functional programming. Writes tests for code. Can debug errors quickly.
  • Strong data visualization skills.
  • Familiarity with one or more machine learning libraries or frameworks such as : PyTorch, Tensorflow.
  • Experience with rational and non-structure databases is highly desirable.
  • Experience using cloud technologies such as AWS with tools such as S3, Lambda, Athena, API Gateway, SageMaker.
  • Strong foundation in data analysis and statistical learning.
  • Must be able to provide evidence of relevant research expertise in the form of presentations, software, technical publications, and / or knowledge of applications.
  • Experience with statistical methodologies and machine learning techniques including neural networks, graphical models, ensemble methods, and natural language processing.
  • Knowledge of generative AI approaches such as large language models, diffusion models, or GANs is desirable.
  • Proficiency with Python and R.
  • Strong data visualization skills.
  • Familiarity with machine learning libraries such as PyTorch, TensorFlow, and scikit-learn.
  • Programming experience in Java, Python, or Perl with knowledge of relational and non-structured databases.
  • Technical proficiency and demonstrated success in scientific creativity, collaboration, and independent thought.
  • Ability to translate research concepts into practical solutions and prototypes.
  • Comfortable working with both technical and non-technical staff.
  • Strong project management skills with the ability to measure success metrics.
  • Leadership experience in technical discussions with senior stakeholders.
  • Must have ability to communicate effectively.
  • Preferences :

  • Candidates in the Raleigh area are preferred so they can be able to work onsite when needed.
  • Candidates with a healthcare industry background are preferred.
  • Physical Demands and Environmental Conditions :

  • Regularly works with a computer for approximately 6-8 hours a day.
  • Must be able to read and understand scientific and complex directions.
  • Technical Proficiencies :

  • Languages : Python , R, SQL, Excel, Java, JavaScript, Spark (Pyspark)
  • Packages : Scikit-learn, Pandas, NumPy, SciPy, TensorFlow, PyTorch, SpaCy, Hugging Face Transformers, Snorkel, H2O, Spark MLlib, Matplotlib, Seaborn, Statsmodels
  • Cloud : AWS (S3, Athena, Glue, EC2, SageMaker, Lambda, etc.), or equivalent cloud platforms
  • Technologies : Git, Jira, Docker
  • Techniques : Both traditional ML (Random Forest, XGBoost, clustering, etc.) and generative approaches (transformer models, diffusion models, GANs) as appropriate for the problem at hand, Machine learning and deep learning fundamentals, Natural language processing and understanding, Computer vision and image analysis, Exploratory data analysis and feature engineering, A / B testing and experimental design, Time series forecasting and anomaly detection, MLOps and model deployment practices, Ethical AI and responsible model development, Experience in Clinical data preferred
  • EDUCATION

  • Advance degree is required in Computer Science, Engineering, Statistics, Math or related field.
  • Must be able to provide evidence of relevant research expertise in the form of presentations, software, technical publications, and / or knowledge of applications.
  • Master with at least 4 years’ experience or Ph.D. with 2 years of experience in a Data science setting.
  • Benefits : Employees regularly scheduled to work 20 or more hours per week are eligible for comprehensive benefits including : Medical, Dental, Vision, Life, STD / LTD, 401(k), Paid Time Off (PTO) or Flexible Time Off (FTO), Tuition Reimbursement and Employee Stock Purchase Plan. Casual, PRN & Part Time employees regularly scheduled to work less than 20 hours are eligible to participate in the 401(k) Plan only. For more detailed information, please  .

    Labcorp is proud to be an Equal Opportunity Employer :

    Labcorp strives for inclusion and belonging in the workforce and does not tolerate harassment or discrimination of any kind. We make employment decisions based on the needs of our business and the qualifications and merit of the individual. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), family or parental status, marital, civil union or domestic partnership status, sexual orientation, gender identity, gender expression, personal appearance, age, veteran status, disability, genetic information, or any other legally protected characteristic. Additionally, all qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law.

    We encourage all to apply

    If you are an individual with a disability who needs assistance using our online tools to search and apply for jobs, or needs an accommodation, please visit our or contact us at For more information about how we collect and store your personal data, please see our .

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