Role Overview
We are hiring a Senior Data Scientist / AI Engineer to design, build and scale production-grade AI solutions, with a strong focus on Generative AI, NLP, and healthcare-related use cases. This role is suited for a hands-on technical leader who can translate complex business and domain problems into reliable AI systems that create value, work closely with cross-functional teams, and mentor high-performing data science talent across multiple geographies.
The ideal candidate brings strong machine learning fundamentals, deep experience with NLP and transformer-based models, practical exposure to LLMs and RAG systems, and the ability to deliver measurable business and operational impact in real-world environments.
Requirements
Key Responsibilities
- Design, build, and deploy end-to-end AI and machine learning solutions, with a focus on GenAI, NLP, and healthcare applications.
- Develop and productionize LLM-based workflows, including prompt engineering, evaluation frameworks, fine-tuning approaches, and Retrieval-Augmented Generation systems.
- Translate ambiguous business and healthcare problems into structured data science solutions with clear success metrics.
- Own the full model lifecycle, including data preparation, experimentation, validation, documentation and articulation of results, deployment, monitoring, and continuous improvement following RAI guidelines.
- Work with large-scale structured and unstructured data, including clinical, operational, claims, member, provider, or other healthcare-related datasets.
- Partner with product, engineering, business, clinical, and compliance stakeholders to ensure solutions are scalable, explainable, secure, and aligned with business needs.
- Lead, mentor, and develop a team of data scientists, and AI engineers, setting high standards for technical quality, analytical rigor, and delivery discipline.
- Drive best practices in model development, code quality, documentation, reproducibility, and responsible AI.
- 8+ years of experience in developing and implementing end-to-end solutions using Machine Learning and AI tools.
- 5+ years of hands-on experience in NLP, deep learning, and transformer-based models.
- 2+ years of practical experience building end-to-end Generative AI solutions, including LLM workflows, fine-tuning, evaluation, and RAG-based systems.
- Strong proficiency in Python and PySpark is mandatory.
- Proven experience building and deploying production-grade ML or AI systems at scale.
- Strong business acumen with the ability to convert complex business problems into practical AI solutions that deliver measurable impact.
- 2+ years of experience leading, mentoring, or managing high-performing data science teams is highly desirable.
- Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Experience working in a matrix organization.
Preferred Qualifications
- Experience in the healthcare domain is highly desirable, especially in areas such as clinical AI, payer/provider analytics, population health, claims, care management, medical operations, or health data platforms.
- Experience working with healthcare data standards, privacy requirements, regulated environments, or responsible AI considerations in healthcare.
- Hands-on experience with Azure, Databricks, or equivalent cloud and data platforms.
- Working knowledge of MLOps, CI/CD for ML, model monitoring, model governance, and scalable deployment patterns.
- Experience optimizing AI systems for accuracy, performance, latency, reliability, cost, and maintainability.
- Exposure to multimodal AI, knowledge graphs, medical text analytics, or clinical decision support use cases is a plus.
What Good Looks Like
- Strong technical depth combined with practical judgment.
- Ability to operate in ambiguous environments and bring structure to complex problems.
- High ownership mindset with a focus on outcomes, not just models.
- Clear communication, strong stakeholder management, and the ability to influence across teams.
- Passion for building AI solutions that are robust, responsible, and meaningful in a healthcare context.
Skills Required
- 8+ years developing and implementing end-to-end ML and AI solutions
- 5+ years hands-on experience in NLP, deep learning, and transformer-based models
- 2+ years practical experience building end-to-end Generative AI solutions including LLM workflows, fine-tuning, evaluation, and RAG systems
- Strong proficiency in Python and PySpark
- Proven experience building and deploying production-grade ML/AI systems at scale
- Excellent written and verbal communication skills
- Experience working in a matrix organization
- 2+ years leading, mentoring, or managing data science teams
- Experience in healthcare domain (clinical AI, payer/provider analytics, claims, population health)
- Hands-on experience with Azure, Databricks, or equivalent cloud/data platforms
- Working knowledge of MLOps, CI/CD for ML, model monitoring, and model governance
- Experience with healthcare data standards, privacy/regulatory requirements, and responsible AI in healthcare
- Exposure to multimodal AI, knowledge graphs, or medical text analytics
What We Do
Enable Data specializes in advanced data, application and cloud solutions working on cutting-edge projects driving innovation and transformation for our customers. We empower our customers to leverage modern solutions to deliver increased value across their business ecosystem. We help clients by providing consulting, managed project and staff augmentation services working with clients across various industries including healthcare, financial, media, insurance, and manufacturing.
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