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 IT Senior 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 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 onsite to Iselin, New Jersey, for 1 week each quarter. This position will include heavy data analysis utilizing our hospital system EPIC Clarity and Caboodle.
Responsibilities A day in the life of a IT Senior 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. Plays a key role in communicating ML/AI methodology and impact to senior management to inform strategic decision-making. Proactively communicates with stakeholders about areas of concern regarding changes in work schedules.
Leads and manages complex projects, including managing multiple stakeholders and teams. Build and maintain relationships with key stakeholders, including senior management and clients. Mentors and coaches junior team members on ML/AI techniques and best practices.
Leads and motivates project teams by setting clear goals and expectations. Builds and maintains strong relationships with key stakeholders across the organization. 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. Minimum of 4+ years of experience working in a data science role; or 5+ years of experience working in a data engineering, analyst, or architecture role.
Extensive Python development experience. Extensive SQL experience. Proficient in developing and interpreting complex statistical models and a wide range of ML models.
Excellent understanding of most aspects of clinical data; Very proficient with querying and using clinical data. Able to deploy custom ML/AI models to a cloud platform. Proficient in writing production code for complex models.
Experience and ability to optimize LLM output with prompt engineering, model fine-tuning, and ability to create RAG pipelines. Can create custom model monitoring solutions as needed. 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: Master's / PhD.
Minimum of 5+ 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 the above description speaks directly to your strengths and capabilities, then please apply today!
Compensation Minimum rate of $171,662.40 Annually HMH is committed to pay equity and transparency for our team members. The posted rate of pay in this job posting is a reasonable good faith estimate of the minimum base pay for this role at the time of posting in accordance with the New Jersey Pay Transparency Act and does not reflect the full value of our market-competitive total rewards package. The starting rate of pay is provided for informational purposes only and is not a guarantee of a specific offer.
Posted hourly rates may be stated as an annual salary in the offer and posted annual salaries may be stated as an hourly rate in the offer, depending on the level and nature of the job duties and credentials of the candidate. The base compensation determined at the time of the offer may be different than the posted rate of pay based on a number of non-discriminatory factors, including but not limited to: Labor Market Data: Compensation is benchmarked against market data to ensure competitiveness.
Years of relevant work experience. Education and
Level of education attained, including specialized certifications, credentials, completed apprenticeship programs or advanced training.
Demonstrated proficiency in relevant skills and competencies. Geographic Location: Cost of living and market rates for the specific location. Internal Equity: Compensation is determined in a manner consistent with compensation ranges for similar roles within the organization.
Budget and Grant Funding: Departmental budgets and any grant funding associated with the job position may impact the pay that can be offered. Some jobs may also be eligible for performance-based incentives, bonuses, or commissions not reflected in the starting rate. Certain positions may also be eligible for shift differentials for work performed on evening, night, or weekend shifts.
In addition to our compensation for full-time and part-time (20+ hours/week) job positions, HMH offers a comprehensive benefits package, including health, dental, vision, paid leave, tuition reimbursement, and retirement benefits. HACKENSACK MERIDIAN HEALTH (HMH) IS AN EQUAL OPPORTUNITY EMPLOYER All qualified applicants will receive consideration for employment without regard to age, race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, breastfeeding, genetic information, refusal to submit to a genetic test or make available to an employer the results of a genetic test, atypical hereditary cellular or blood trait, national origin, nationality, ancestry, disability, marital status, liability for military service, or status as a protected veteran.
Our Network Hackensack Meridian Health (HMH) is a Mandatory Influenza Vaccination Facility As a courtesy to assist you in your job search, we would like to send your resume to other areas of our Hackensack Meridian Health network who may have current openings that fit your skills and experience.