Data Scientist

Role Overview

Elder Research seeks a Data Scientist to join its analytics team in the Raleigh, NC or Washington, DC market. This is a hybrid role requiring 1–2 days onsite per week and focuses on end-to-end development and deployment of predictive, production-ready models.

Responsibilities

• Lead data science initiatives end-to-end, including:
  • Time series forecasting
  • Natural Language Processing (NLP)
  • Predictive model building, training, and maintenance
• Requirements discovery & data “sleuthing” (about 10–20% of the role) to connect ambiguous business problems to underlying data patterns
• Deliver automation and insights, including:
  • Anomaly detection
  • Case prediction
  • Recommending and building automation around manual processes
• Full-lifecycle ownership using data engineering skills to:
  • Integrate data, deploy solutions
  • Ensure scalability and operational reliability
  • Troubleshoot deployment issues when needed
• Collaborate and communicate with technical and non-technical stakeholders and client partners; serve as a trusted advisor
• Mentor more junior data scientists

Requirements (Minimum)

• 5+ years of experience as a Data Scientist
• Bachelor’s degree in a relevant field (e.g., statistics, computer science, economics, mathematics, analytics, data science)
• Proficiency in Python for data analysis and modeling
• Strong SQL for deep dataset analysis
• Hands-on experience with AWS and production pipeline tooling, including:
  • Amazon SageMaker, Lambda, Step Functions, Glue, S3, Athena
• Knowledge of CI/CD, Git version control, and Infrastructure-as-Code
• Experience with logging/monitoring/alerting (e.g., CloudWatch)
• Understanding of AWS IAM roles, policies, and security best practices
• Curiosity and ability to connect technical work to real-world impact

Preferred Qualifications

• Familiarity with AWS CDK and/or TypeScript
• Strong ability to define and drive projects from ambiguity to concrete outcomes
• Excellent consultative and communication skills with clients
• Ability to work autonomously in a flexible environment
• MS or PhD in relevant fields; experience with advanced statistical concepts (bias, weighting, missing/outlier handling, exploratory analysis, sampling considerations)