RRemoteville
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Data Scientist

Skills
Computer ScienceContinuous ImprovementData AnalyticsData ServicesDatabasesEnterprise SystemsHealth Informatics
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • Bachelor's degree in Computer Science Data Science Statistics Mathematics Engineering Health Informatics Public Health or related field; master's preferred
  • Two to four years of experience developing data science analytics machine learning or AI solutions in applied project environments
  • Strong proficiency in Python and SQL for data preparation analytics model development testing and deployment
  • Experience developing and evaluating machine learning models including feature engineering train validation test design performance assessment and error analysis
  • Working knowledge of NLP and modern AI concepts including LLMs embeddings RAG prompt engineering retrieval approaches and output evaluation
  • Experience creating dashboards or visual analytics using Power BI Tableau Python or comparable tools
  • Familiarity with API-based solutions and integration of data machine learning or AI services into broader applications or enterprise environments
  • Experience collaborating in a Git-based team environment using code reviews Agile tickets and software development best practices
  • Ability to work across notebook-based browser-based and local development environments learn unfamiliar technologies quickly manage competing priorities and deliver assigned work independently
  • Strong communication and problem-solving skills including proactive status reporting early escalation of risks and blockers and effective communication with technical and non-technical audiences
  • Must be a U.S. Citizen and able to obtain and maintain a SECRET security clearance

Nice to have

  • Consultative
  • Collaborative
  • Independent
  • Detail-oriented
  • Problem-solving

Day to day

  • Develop and deploy analytics machine learning NLP and AI solutions for mission and client objectives
  • Build generative AI and RAG components using LLMs embeddings vector databases retrieval strategies prompt engineering and cloud AI services
  • Analyze complex data and deliver predictive prescriptive and decision-support insights across multidisciplinary healthcare focused project teams