Principal Data Scientist

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Principal Data Scientist

Location: Ideal candidates will be able to report to our Pulse Point location at 5650 University Pkwy, Winston-Salem, NC 27105.

This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace.

Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.

Work Hours: Monday to Friday, 8:00 am to 5:00 pm

The Principal Data Scientist is responsible for leading the development and implementation of predictive modeling algorithms and techniques to solve business problems and optimize member experiences.

How You Will Make an Impact: 

• Serve as the methodology-expert on the team and provide guidelines to team for applying appropriate algorithms or solutions to approach different data challenges.

• Coach junior team members on various data science techniques..

• Keep abreast of the latest enhancements and innovations within the areas of data science and big data processing.

• Lead the design and execution of predictive modeling projects to address specific business problems determined by consultation with business partners.

• Provide guidance to the team on working with data-sets of varying degrees of size and complexity including both structured and unstructured data.

• At the expert level, piping and processing massive data-streams in distributed computing environments such as Hadoop to facilitate analysis.

• Leads batch and real-time model scoring to drive actions.

• Leads the development of proprietary predictive modeling algorithms to build customized solutions that go beyond standard industry tools and lead to innovative solutions.

• Leads communication and publish results and address constraints/limitations with business partners.

• Determines the continuous improvement opportunities of current predictive modeling algorithms.

• Proactively collaborates with business partners to determine identified population segments and develop actionable plans to enable the identification of patterns related to quality, use, cost and other variables that have a broad impact.

Minimum Requirements:

• Bachelor's degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative discipline.

• Seven (7) years in any occupation with predictive analytics experience.

Experience Requirements:

• Seven (7) years in any occupation with predictive analytics experience must include:

• • End-to end predictive modeling and large-scale data preparation (ETL, feature engineering, training/validation, scoring) using Python, Apache Spark (PySpark/Spark SQL), PostgreSQL, and advanced SQL;

• • OS-level development, system control, dependency management, reproducible environments, and ML pipeline runtime setup using advanced Linux and Python environment tools (e.g., Anaconda/conda, pip/venv, airflow);

• • Distributed ETL and processing for massive structured and unstructured datasets using Hadoop and Hive;

• • Enterprise cloud data access, storage, and compute for analytics and model execution using AWS;

• • Supervised ML development, tuning, and evaluation using scikit-learn and XGBoost;

• • Regression/GLMs, hypothesis testing, confidence interval interpretation, ANOVA, residual diagnostics, and evaluation methods (e.g., propensity score matching) using advanced statistical modeling and inference;

• • Customized deep learning model development using tools beyond standard tools (e.g., PyTorch);

• • Parallelization and performance optimization for compute-intensive workloads using multicore/OpenMP concepts;

• • Code versioning, branching, collaboration, and release management using Git;

• • Developing, testing, and validating complex SQL for analytics pipelines using professional SQL IDEs/DB clients (e.g., JetBrains DataGrip); and

• • Experience with analyses leveraging electronic medical records, claims, and health coverage eligibility data.

Alternate Education / Experience Requirements:

• Employer will accept a Master's degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative discipline and

• Five (5) years in any occupation with predictive analytics experience. Must have skills listed above

APPLY:                              https://careers.elevancehealth.com/

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