Data Scientist & Engineer

NYU Langone Health • New York, NY

1d • $84,578 - $110,250

About The Position

NYU Grossman School of Medicine is seeking a Data Scientist Analyst / Engineer to work within the Division of Applied AI Technologies at NYU Langone Health. The role contributes to analytics initiatives by partnering with clinicians, operations teams, and administrative teams to develop impactful data-driven healthcare solutions. The position involves applying machine learning and informatics methods to complex clinical data, developing and deploying data products, and supporting predictive modeling and analytics across the healthcare organization.

Requirements

• Master’s degree in a quantitative discipline such as Biomedical Informatics, Computer Science, Machine Learning, Applied Statistics, Mathematics, or a similar field.
• At least 3 years of experience in machine learning or data science.
• Proficiency in at least one programming language, such as Python or R, and machine learning tools such as scikit-learn or R.
• Knowledge of predictive modeling and machine learning, including design, development, evaluation, deployment, and scaling to large datasets.
• Familiarity with big data computing models such as Hadoop/MapReduce and Spark.
• Knowledge of relational databases and SQL, and NoSQL databases such as MongoDB.
• Good understanding of software engineering principles and experience integrating modern software architectures.
• Knowledge and some experience with operational aspects of software development and deployment, including automation, testing, virtualization, and container technology.
• Knowledge of clinical and operational aspects of healthcare delivery.
• Excellent written and oral communication skills for a variety of audiences.
• Ability to communicate effectively with all levels of the organization.

Nice To Haves

• PhD in a quantitative field such as Biomedical Informatics, Computer Science, Machine Learning, Applied Statistics, Mathematics, or a similar field, plus 2 years of experience.
• Demonstrated skills in designing and implementing complex machine learning models.
• Demonstrated knowledge of software engineering and operational skills through prior projects.

Responsibilities

• Design and build data solutions using machine learning and informatics methods.
• Work with large, complex, and noisy clinical datasets to address healthcare problems.
• Build workflows to collect, store, clean, and process structured and unstructured data, and verify their integrity and suitability for business processes and analytics systems.
• Deploy and integrate data products into the healthcare infrastructure.
• Prepare and present oral and written reports on processes, models, evaluation, and impact, including ROI.
• Lead high-priority data-oriented projects through development, deployment, and evaluation.
• Collaborate with data scientists, engineers, and clinically trained professionals to test new approaches and support implementation, maintenance, and improvement of predictive models.
• Collaborate with the broader NYULMC healthcare community and contribute to predictive modeling and analytics efforts.
• Establish metrics, run experiments, and analyze the incremental impact of efforts to drive adoption and engagement.
• Contribute to data science best practices and mentor team members.
• Quantify the impact of model improvements and communicate trade-offs to stakeholders.
• Build evaluation frameworks, validate model behavior prospectively and silently, and oversee ongoing maintenance.
• Design systems, infrastructure, abstractions, and processes to accelerate development of future projects.
• Manage and plan go-live activities and define steps to support timely delivery.
• Balance research quality with production readiness, iterate quickly, and determine when a minimum viable product is preferable to an extended research project.
• Contribute ideas and innovations to solve internal and stakeholder problems.

Benefits

• Comprehensive benefits and wellness package.
• Financial security benefits.
• Generous time-off program.
• Employee resource groups for peer support.
• Employee wellness program covering physical, mental, nutritional, sleep, social, financial, and preventive care.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level