IT Lead Data Scientist
Overview
Our team members are the heart of what makes us better.
At Hackensack Meridian Health we help our patients live better, healthier lives — and we help one another to succeed. With a culture rooted in connection and collaboration, our employees are team members. Here, competitive benefits are just the beginning. It’s also about how we support one another and how we show up for our community.
Together, we keep getting better - advancing our mission to transform healthcare and serve as a leader of positive change.
The Information Technology (IT) Lead Data Scientist will join a collaborative team of extremely talented Analysts, Engineers, Designers, and Managers across the Hackensack Meridian Health (HMH) network. This role requires using data analysis, applied mathematics, machine learning (ML), and large language models to build next-generation predictive solutions and artificial intelligence (AI) tools that enable clinicians and other end-users within the organization to perform their work more efficiently and effectively. In this role, there is a strong emphasis on using the agile development methodology to rapidly iterate and deploy impactful solutions within the healthcare organization.
This position will require you to travel 1 full week onsite per quarter and 1 additional onsite day per month.
Responsibilities
A day in the life of a Information Technology (IT) Lead Data Scientist at Hackensack Meridian Health includes:
- Work with HMH stakeholders to document and understand their objectives and ideate how AI/ML solutions might achieve those objectives.
- Perform exploratory data analysis to understand the data available related to a particular business objective and if that data lends itself to the creation of an AI/ML solution that might achieve that business objective.
- Optimizing Large Language Model (LLM) output with prompt engineering; building (RAG) pipelines.
- Build AI/ML models that attempt to address a business objective given the data available; explore the model space to understand the optimal model for the particular use case and what the performance characteristics are.
- Create repeatable, interpretable, and scalable models that can be seamlessly incorporated into analytic data products.
- Engineer features by using business acumen to find new ways to combine data sources.
- Write production-quality pipeline code used to load data, execute the AI/ML model, and store the results.
- Perform analyses of AI/ML models and systems, such as fairness, bias, and equity audits; performance analyses; impact assessments; and interpretability reports.
- Develop and commit Python code in such a way that it works in harmony with the code and systems being developed by the team's data engineers, software engineers, and data analysts.
- Play a key role in communicating ML/AI methodology and impact to senior management to inform strategic decision-making. Demonstrate strong communication and interpersonal skills that will be used in leading and motivating team members.
- Proactively communicate with stakeholders about areas of concern regarding changes in work schedules. Track and mentor individual team members about time and work management.
- Develop and implement ML/AI strategies that align with business objectives. Manage multiple projects. Establish thought leadership within the organization.
- Create a culture of collaboration, innovation, and continuous improvement within the team. Ensure overall team performance in the delivery of ML/AI solutions.
- Other duties and/or projects as assigned.
- Adheres to HMH Organizational competencies and standards of behavior.
Qualifications
Education, Knowledge, Skills and Abilities Required:
- Bachelor's degree in STEM or another related/relevant field of study; and Master's degree in data science-related area.
- Minimum 6+ years of experience working in a data science role.
- Expert-level Python development experience.
- Expert-level SQL experience.
- Proficient in developing and interpreting complex statistical models.
- Deep expertise in at least one aspect or area of data acquisition, cleaning, and curation; EDA; or statistical analysis.
- Excellent understanding of most aspects of clinical data; Very proficient with querying and using clinical data; Deep expertise in at least one aspect or area of clinical data.
- Excellent understanding of a wide range of ML models. Able to improve model performance with complex feature engineering and hyperparameter tuning. Ability to design and implement complex machine learning pipelines. Deep expertise in at least one aspect of machine learning.
- Expertise in prompt engineering methodology, model fine-tuning, and ability to create RAG pipelines.
- Can create custom monitoring solutions as needed. Deep expertise in at least one area of ML Ops.
- Work effectively with team members and technical and non-technical stakeholders.
- Excellent written and verbal communication skills.
- Proficient computer skills including but not limited to Microsoft Office and Google Suite platforms.
Education, Knowledge, Skills and Abilities Preferred:
- PhD degree.
- Minimum of 6+ years of data analysis experience in healthcare.
- Proficiency in Epic Clarity clinical data models.
- Experience with Google Cloud Platform (Big Query, VertexAI, etc).
- Experience with Git and GitHub
- Experience with Docker.
Licenses and Certifications Preferred:
- Epic Clarity Data Model.
- Epic Clarity Clinical Data Model.
- Google Machine Learning Engineer Certification.
If you feel that the above description speaks directly to your strengths and capabilities, then please apply today!