Data Scientist

Our partner is looking for a Senior Data Scientist based in the United States. This is a senior individual contributor role focused on building production-grade AI, machine learning, and NLP solutions in healthcare.

• Lead AI, ML, and NLP initiatives end to end, covering problem framing, solution design, model development, validation, deployment, monitoring, and ongoing production maintenance.
• Develop LLM-powered applications that automate complex, high-volume workflows while balancing accuracy, response time, throughput, and inference costs through model selection, caching, prompt engineering, and related techniques.
• Design evaluation datasets and automated evaluation pipelines to measure model quality, error rates, and performance across clinical and financial content, identifying regressions caused by changes in models, prompts, or data.
• Build and maintain production-grade data foundations, including ETL/ELT pipelines and feature datasets sourced from PostgreSQL transactional systems and Redshift data warehouses.
• Establish strong standards for data quality, reliability, documentation, lineage, and maintainability across analytical and machine learning data workflows.
• Collaborate with clinicians, pharmacists, and other domain experts to establish ground truth, assess edge cases, and validate model behavior against real-world clinical workflows.
• Ensure AI and ML solutions meet appropriate healthcare standards and regulatory requirements, including HIPAA, while monitoring for bias, safety issues, and performance drift.
• Serve as technical lead on complex, ambiguous projects by defining approaches, establishing best practices, setting technical direction, and influencing broader engineering and data strategy.
• Coach and mentor data scientists through technical pairing, design reviews, code reviews, and constructive feedback while contributing to technical hiring and team development.
• Communicate complex analytical results and technical concepts effectively to technical and non-technical audiences, including executive leadership, through presentations, reports, and visualizations.
• Partner closely with software architects and engineering teams to ensure models and data products integrate effectively into production systems and meet platform requirements.

• Master’s or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative discipline.
• 5+ years of professional experience in data science, machine learning, and NLP, with a demonstrated track record of delivering models into production environments.
• Advanced proficiency in Python and SQL.
• Hands-on experience developing and orchestrating ETL/ELT pipelines using technologies such as dbt, Airflow, and AWS data services including Glue, DMS, Lambda, and S3.
• Strong understanding of incremental data loads, idempotency, data quality testing, documentation, and data lineage.
• Strong software engineering fundamentals, including modular and tested production-quality Python, Git-based workflows, code reviews, Docker, and CI/CD.
• Experience productionizing and monitoring machine learning models in AWS environments, including model registries, ML CI/CD, versioning, and post-deployment monitoring using tools such as SageMaker and MLflow.
• Demonstrated experience building and evaluating LLM-powered applications, including solutions using models such as Claude through Amazon Bedrock, prompt design, retrieval and RAG pipelines, and systematic evaluation of output quality.
• Proven ability to independently scope ambiguous technical problems and deliver solutions from conception through production.
• Demonstrated project leadership and experience coaching or mentoring other data scientists.
• Excellent analytical, problem-solving, communication, and collaboration skills, with the ability to operate effectively in a fast-paced environment.
• Healthcare or insurance industry experience is preferred.
• Familiarity with healthcare data standards such as FHIR, HL7v2, and X12 and clinical vocabularies including RxNorm, NDC, ICD-10, and SNOMED is a plus.
• Experience modeling analytical data for Amazon Redshift or comparable columnar MPP platforms, extracting from PostgreSQL, and writing performant SQL against large datasets is preferred.
• Ability to analyze query plans and optimize slow SQL queries independently.
• Experience deploying containerized applications and models using Docker and cloud-managed infrastructure such as SageMaker endpoints, ECS, or Lambda; Kubernetes experience is a plus.
• Comfortable working primarily at a desk and traveling approximately 10% for client sites, conferences, or internal meetings.

• Competitive base salary of $140,000–$170,000, with exact compensation determined by skills and experience.
• Eligibility for a discretionary performance-based bonus.
• Medical, dental, and vision insurance.
• 401(k) eligibility after three months, with a 50% company match on the first 5% of s