Principal Data Scientist

Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission critical decision making for various areas of the organization. Understand business needs and identify opportunities for new products, services, and process optimization to meet business objectives through the use of cutting-edge data science. Create descriptive, predictive, and prescriptive models and insights to drive impact across the organization. Regarded as an advanced professional in the data science field. Conduct complex work under minimal supervision and with wide latitude for independent judgment. Mentor lower level staff.

- 6+ years of experience with requisite competencies
- Complete knowledge and full understanding of specialization
- Statistics, machine learning , data mining, data auditing, aggregation, reconciliation, and visualization
- Programming, data modeling, simulation, and advanced mathematics
- SQL, R, Python, Hadoop, SAS, SPSS, Scala, AWS
- Model lifecycle execution
- Technical writing
- Data storytelling and technical presentation skills
- Research Skills
- Interpersonal Skills
- Advanced knowledge of procedures, instructions and validation techniques
- Model Development
- Communication
- Critical Thinking
- Collaborate and Build Relationships
- Initiative with sound judgement
- Technical (Big Data Analysis, Coding, Project Management, Technical Writing, etc.)
- Independent Judgment
- Problem Solving (Identifies the constraints and risks)
- Bachelor's Degree in Data Science, Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields

Desired Qualifications

- Master's/PhD Degree in Data Science, Statistics, Mathematics, Computers Science, or Engineering
- 6+ years of experience applying advanced analytics, machine learning, and statistical methods to solve complex business problems and influence strategic decisions.
- Strong understanding of the end-to-end data science lifecycle, including data quality assessment, feature engineering, model development, validation, deployment, monitoring, and governance.
- Expertise in Voice of the Member, customer feedback, survey, complaint, contact center, or digital interaction data, with the ability to turn unstructured feedback into actionable insights.
- Experience applying Natural Language Processing (NLP), text analytics, sentiment analysis, topic modeling, and/or Large Language Models (LLMs) to understand customer needs, behaviors, and experiences.

Additional Information

Hours:

- Monday - Friday, 8:00AM - 4:30PM EST

Location:

- 820 Follin Lane, Vienna, VA 22180