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 Digital Technology Services (DTS) 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.

A day in the life of a Digital Technology Services (DTS) 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.
• 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.
• 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.
• Contribute to the analyses of AI/ML models and systems, such as fairness, bias, and equity audits; performance analyses; impact assessments; and interpretability reports.
• Deploy standard models (e.g., sk-learn) to a cloud platform and implement model monitoring solutions.
• 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.
• Communicate findings independently to a wider range of stakeholders, including non-technical audiences. Effectively present complex technical concepts in a compelling and engaging way.
• Actively participate in planning sessions to provide estimates for the effort required. Clearly communicate work status to stakeholders. Keep track of multiple projects. Works independently.
• Articulate goals, establish timelines and plan and implement processes to achieve goals.
• Provide constructive feedback to team members and their projects in the form of code reviews and actionable working session suggestions.
• Other duties and/or projects as assigned.
• Adheres to HMH Organizational competencies and standards of behavior.

Education, Knowledge, Skills and Abilities Required:

• Bachelor's degree in STEM or another related/relevant field of study.
• Minimum of 2+ years of experience working in a data science role; or 3+ years of experience working in a data engineering, analysis, or architecture role.
• Intermediate Python development experience.
• Intermediate SQL experience.
• Proficient in data cleaning and exploratory data analysis with the ability to identify, interpret, and communicate patterns in data. Has a solid understanding of fundamental statistical modeling techniques.
• Understand concepts about patient class, encounters, demographics, billing codes, and comorbidities and can query and use clinical data.
• Proficient in ML model development and evaluation.
• Experience and ability to optimize LLM output with Prompt engineering.
• Understand intermediate concepts of model monitoring.
• 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 4+ years of data analysis experience in healthcare.
• Experience with Google Cloud Platform (Big Query, VertexAI, etc).
• Experience with Git and GitHub.
• Experience with Docker.

 

If you feel that the above description speaks directly to your strengths and capabilities, then please apply today!     

Starting at $131,144.00 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.
Experience: Years of relevant work experience.
Education and Certifications: Level of education attained, including specialized certifications, credentials, completed apprenticeship programs or advanced training.
Skills: 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.