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Our client is a forward-thinking organization in the healthcare/technology sector focused on leveraging data, AI, and advanced analytics to drive operational excellence and innovation. They are seeking a Data Science Lead to strengthen their data science practice and deliver high-impact AI/ML solutions.
Job Responsibility
Defining and driving the data science and AI roadmap, aligning model development priorities with business objectives and product strategy.
Leading end-to-end delivery of ML and AI solutions — from problem framing, data discovery, and model design through validation, deployment, and performance monitoring.
Translating ambiguous business problems into well-scoped data science workstreams, identifying quick wins alongside longer-term strategic initiatives.
Designing and implementing NLP pipelines for use cases such as entity extraction, semantic mapping, classification, and retrieval-augmented generation (RAG).
Building and maintaining forecasting and predictive models to support operational and strategic decision-making.
Conducting current-state assessments of data architecture, sources, and quality
defining future-state data models and governance standards.
Partnering closely with Product, Engineering, and business stakeholders to clarify requirements and define measurable success criteria.
Mentoring data analysts and junior data scientists, and driving a culture of continuous learning and responsible AI.
Requirements
Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Economics, or a related quantitative field (or equivalent professional experience).
5+ years of experience in data science, data analytics, or a related discipline, including production ML/AI deployments.
Strong proficiency in Python for data science workflows, including pandas, scikit-learn, and NLP libraries (e.g., spaCy, Hugging Face Transformers).
Proven experience designing and delivering NLP pipelines and/or forecasting models in a business context.
Solid command of SQL for data querying, transformation, and analysis.
Experience with BI and reporting tools, particularly Power BI (including data modeling and DAX).
Demonstrated ability to communicate analytical findings clearly to non-technical stakeholders.
Experience working in regulated industries (healthcare, finance, or similar) with understanding of compliance and data governance requirements (e.g., HIPAA, GDPR).
Full US Work Authorization (no sponsorship provided)
Nice to have
7+ years of data science or analytics experience, including a team lead or principal contributor role.
Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and prompt engineering.
Familiarity with cloud-based ML platforms (GCP, AWS, or Azure) and MLOps practices.
Working knowledge of process optimization frameworks such as Lean Six Sigma.
Exposure to clinical data standards or health data interoperability.
PL-300 Power BI Data Analyst certification is a plus.