Senior Data Scientist (Hybrid as needed)

Northwell•New Hyde Park, NY

8h•Hybrid

About The Position

You will plan, implement, and maintain data-driven solutions that will directly impact patients and healthcare delivery. This role will require advanced proficiency in understanding stakeholder needs, planning and implementation of data science solutions (involving machine learning, natural language processing, deep learning, generative AI). Have an expert-level understanding of clinical data and acts as the main liaison between the data science team, adjacent engineering teams, as well as non-engineering clinical and administrative stakeholders. Oversees the validation of models using appropriate metrics and delivers actionable insights that meaningfully improve patient care and safety. Ensures that projects and their outputs enhance clinical quality, patient safety, and institutional efficiency, focusing on all aspects of data science, including data gathering and wrangling, exploratory data analysis, data modeling and machine learning, and model implementation and evaluation.

Requirements

Bachelor's Degree required, or equivalent combination of education and related experience.
3-5 years of relevant experience, required.

Nice To Haves

Clear and effective communication and presentation skills are highly preferred
Comfortable presenting to non-technical/clinical stakeholders and executive leadership
Strong portfolio of data science projects with organizational-level impact (healthcare related preferred)
Experience with cloud computing (GCP, Vertex AI preferred)
Strong experience with orchestration/ETL pipelines (e.g. Airflow, Prefect, Luigi, Kubeflow) with preference for Airflow
Strong experience with DevOps/MLOps (e.g. containerization, CI/CD, feature stores, data lineage)
Advanced/expert level proficiency in statistical analysis, machine learning techniques, model evaluation
Advanced/expert level proficiency in modern machine learning frameworks (e.g. scikit-learn), deep learning frameworks (e.g. Pytorch)
Advanced/expert level experience in training/deploying embedding models, fine-tuning large language models (various tasks), retrieval-augmented generation, prompt and context engineering, and evaluation of generative AI systems

Responsibilities

Ready to own the end-to-end lifecycle of complex data science projects/programs including problem scoping, due diligence, evaluation/validation/model design and development, deployment to production systems, monitoring prediction output, and measuring value
Serve as the primary point of contact between the data science team and clinical, research, and administrative stakeholders
Have strong communication skills to act as the bridge between technical and non-technical team members and stake holders
Support leadership in technical and strategic analyses for decision making related to machine learning/AI
Mentor and teach junior team members as well as non-data science team members
Develop and enforce coding, documentation, governance standards
Guides the design, implementation, and maintenance of data science models and applications.
Guides team members to apply data science methodologies, including predictive modeling and machine learning, data analytics and visualization, and usability and design, to departmental, service line, and enterprise applications and functions.
Synthesizes complex data-related problems into actionable business and/or clinical strategy, and communicate findings to appropriate end-users and stakeholders.
Develops specifications to support the design of new or modified data science projects, with a focus on data-driven optimization, enhancement, and development.
Evaluates projects, systems, and initiatives at the department, service line, and enterprise level; ensures projects and their outputs enhance clinical quality, patient safety, and institutional efficiency, focusing on all aspects of data science, including data gathering and wrangling, exploratory data analysis, data modeling and machine learning, and model implementation and evaluation; ensures high quality execution of all proposed projects.
Knowledgeable in present and planned data science projects and maintains voice of the customer in all project initiatives.
Serves as the link between the clinical staff (customer) requirements and IS capabilities.
Assists in ensuring that systems are implemented to support organization initiatives and goals to improve the quality of patient care, to maximize patient safety, and to provide operational efficiencies.
Serves as a resource to the leadership; demonstrates familiarity with current hospital information systems.
Operates under limited guidance and work assignments involve moderately complex to complex issues where the analysis of situations or data requires in-depth evaluation of variable factors.
Performs related duties as required. All responsibilities noted here are considered essential functions of the job under the Americans with Disabilities Act. Duties not mentioned here, but considered related are not essential functions.