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CareSource
CareSource
1001 – 5000 Darbinieki
H1B vīzas sponsorsApdrošināšanaVeselības apdrošināšanaVeselības aprūpe
CareSource ir veselības apdrošināšanas uzņēmums, kas apkalpo savus biedrus, izmantojot Medicaid, Marketplace un Medicare Advantage plānus. Tā piedāvātais segums un atbalsta pakalpojumi ir paredzēti dažādām grupām, tostarp pieaugušajiem un ģimenēm ar zemiem ienākumiem, bērniem, grūtniecēm, senioriem un cilvēkiem ar invaliditāti. CareSource nodrošina arī zobārstniecības, redzes, dzirdes un aptiekas pakalpojumus, kā arī COVID-19 atbalsta resursus. Tiešsaistes un mobilie rīki palīdz biedriem pārvaldīt savu veselības aprūpi.
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Vakances uzņēmumā

Applied AI Scientist IV – Remote

Lead enterprise AI, NLP, and generative AI initiatives for CareSource’s healthcare operations. Shape AI strategy, governance, predictive analytics, and production deployment across the organization.

USAmerikas Savienotās Valstis
113 000 $ – 197 700 $ / gads
AttālinātiPilna slodzeVecākais speciālistsVadošais speciālistsNepieciešamā Valoda: angļuMākslīgā intelekta pētnieksMašīnmācīšanās inženieris
AWSAzureGoogle Cloud PlatformMākonisPythonSQL

Apraksts

  • Set technical direction for designing, developing, and operationalizing advanced AI solutions that improve healthcare operations, patient outcomes, and organizational performance.
  • Assess emerging AI technologies and establish strategies for enterprise adoption.
  • Analyze unstructured healthcare data with natural language processing and deep learning methods.
  • Guide AI solutions from initial concept through large-scale production deployment.
  • Shape enterprise AI roadmaps and strategy through technical expertise and strategic partnerships.
  • Create technical standards, reusable frameworks, best practices, and governance for AI development, deployment, monitoring, and optimization.
  • Lead complex NLP, predictive analytics, and applied AI programs across multiple business areas.
  • Partner with IT, risk adjustment, program integrity, HEDIS, healthcare operations, finance, and clinical teams.
  • Build and implement predictive models, algorithms, and statistical methods using large healthcare datasets.
  • Develop evaluation approaches for machine learning and large language model solutions, covering quality metrics, bias and safety checks, and post-launch monitoring.
  • Perform data cleansing, feature engineering, exploratory analysis, and rigorous statistical analysis.
  • Establish KPIs, metrics, dashboards, and stakeholder reports that support business decisions.
  • Advise senior leaders using insights from predictive modeling and data analysis.
  • Maintain HIPAA and PHI compliance, data integrity, model governance, and comprehensive documentation.
  • Act as a subject matter expert in AI, machine learning, NLP, generative AI, and emerging technologies.
  • Mentor applied AI scientists, data scientists, and technical teams through code reviews, technical coaching, and architecture guidance.
  • Assess responsible AI practices, healthcare AI regulations, and governance obligations.
  • Handle additional job-related responsibilities as assigned.

Prasības

  • Bachelor’s degree in data science, mathematics, statistics, engineering, computer science, or a related field is required.
  • Comparable relevant work experience may substitute for the required education.
  • A master’s degree is preferred.
  • At least eight years of experience in predictive analytics, data science, or a related discipline is required.
  • At least three years of healthcare industry experience is required.
  • At least three years of experience with cloud platforms such as Azure, AWS, or GCP and modern data platforms such as Databricks or Snowflake is required.
  • At least three years of experience developing and deploying NLP and generative AI solutions in healthcare is required.
  • Experience leading technical efforts, guiding architecture, and mentoring scientific teams is required.
  • Expertise in agentic AI, LLM architectures, prompt engineering, retrieval-augmented generation, evaluation methods, and AI solution design.
  • Advanced MLOps and LLMOps expertise, including deployment, monitoring, experiment tracking, reproducibility, CI/CD, and governance.
  • Advanced understanding of model risk management, AI governance, responsible AI, and healthcare AI regulatory considerations.
  • Expertise in statistical learning, machine learning, predictive analytics, and scientific computing with Python and/or R.
  • Expertise in data manipulation, visualization, and SQL.
  • Ability to conduct advanced statistical analysis and modeling, including linear and nonlinear regression, sampling, and Markov chains.
  • Experience designing document intelligence, OCR, and information extraction solutions with modern AI technologies.
  • Expertise in AI architecture, API integration, and production-grade AI application deployment.
  • Detailed knowledge of healthcare data such as medical and pharmacy claims, EMR, HIE, UM, demographic, and population data.
  • Understanding of healthcare operations, payer and provider models, and industry trends.
  • Proficiency in feature engineering and exploratory data analysis.
  • Excellent analytical, problem-solving, and critical-thinking abilities.
  • Strong technical leadership, influencing, and program coordination skills.
  • Excellent written, verbal, and presentation communication skills.
  • No licensure or certification is required.
  • The role involves a general office environment and may require sitting or standing for extended periods.
  • Occasional travel of up to 15% may be required.

Priekšrocības

  • A bonus linked to company and individual performance may be available.
  • Comprehensive total rewards package.
  • Equal opportunity workplace committed to belonging and support.
  • Up to 15% travel for meetings, training, and conferences.

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