Data Scientist II- Pulmonary

Description

As a Data Scientist II, work closely with clinical leads and product sponsors to deliver an ML project from beginning to end, including designing, developing, testing the data solutions, and independently conducting silent and active pilot runs

Responsibilities

• Collect, clean, and curate large and complex data sets from various sources to ensure it is suitable for machine learning tasks
• Lead the design, development, and optimization of machine learning applications to solve complex optimization problems
• Oversee data collection, preprocessing, and feature engineering to ensure high-quality datasets for model training
• Work with clinical leads and product owners to translate the optimization problem into product development design
• Design and run active pilot to measure usability, adoption, model performance and impact
• Stay updated on the latest advancements in ML and AI and implement novel algorithms and techniques when appropriate.
• Collaborate with the engineering team to deploy machine learning models into production environments, ensuring scalability and reliability.
• Mentor and guide junior members of the ML team, fostering a culture of learning and innovation.
• Collaborate cross-functionally with stakeholders to understand and address operational needs through machine learning solutions
• Research: Participate in research initiatives and contribute to publications and patents
• Effectively communicates statistical and technical ideas and results to non-technical stakeholders in written and verbal form to ensure decision points and their impact are clearly understood by all audiences
• Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies.  Tracks and reports progress.  Keeps stakeholders apprised of project status and implications for completion.
• Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication.
• Mentor other analysts on how to a) determine appropriate statistical analysis methods, b) leverage appropriate programing languages and tools, and c) generate and interpret statistical analysis outputs.
• Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.
• Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.
• Works closely with IT on the ongoing improvement of Mount Sinai’s integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.
• Demonstrates advanced level proficiency with the principles and methodologies of process improvement. Applies these in the execution of responsibilities in support of a process focused approach.
• Other duties as assigned.

Qualifications

• Master's or Ph.D. degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Information Technology, Mathematics, Physics) or equivalent practical experience
• 4+ years of work experience in data science, software engineering, or data analysis
• 2+ years of hands-on experience with Scala and Python, including documentation for reproducibility
• 2+ years of hands-on experience with database languages (e.g., SQL, NoSQL)
• Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques
• Applied experience in ML fields, such as natural language processing, computer vision, and statistical learning theory
• Experience handling terabyte-sized datasets, exploring data to discover hidden patterns, using data visualization tools, and leveraging GPUs for model development
• Proficiency in articulating technical concepts to diverse audiences, both technical and non-technical, and delivering data-driven presentations.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP)
• Experience with version control systems (e.g., Git)
• Knowledge of big data technologies (e.g., Hadoop, Spark)
• Self-motivated with a demonstrated ability to work independently, and to exercise independent judgment in developing complex techniques or programs in a dynamic environment.

Preferred Qualifications                                                                                                      

• Publications or presentations in recognized journals or conferences
• Deep technical skills, 2+ years of experience in running active pilot and business savvy to interface with product owner and users working group
• Deep knowledge and hands-on experience in agile project management

Employer Description

Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai’s unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time — discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients’ medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report’s “Best Children’s Hospitals” ranks Mount Sinai Kravis Children's Hospital among the country’s best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek’s “The World’s Best Smart Hospitals” ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

Compensation

The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $120000 - $180060 Annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

• Collect, clean, and curate large and complex data sets from various sources to ensure it is suitable for machine learning tasks
• Lead the design, development, and optimization of machine learning applications to solve complex optimization problems
• Oversee data collection, preprocessing, and feature engineering to ensure high-quality datasets for model training
• Work with clinical leads and product owners to translate the optimization problem into product development design
• Design and run active pilot to measure usability, adoption, model performance and impact
• Stay updated on the latest advancements in ML and AI and implement novel algorithms and techniques when appropriate.
• Collaborate with the engineering team to deploy machine learning models into production environments, ensuring scalability and reliability.
• Mentor and guide junior members of the ML team, fostering a culture of learning and innovation.
• Collaborate cross-functionally with stakeholders to understand and address operational needs through machine learning solutions
• Research: Participate in research initiatives and contribute to publications and patents
• Effectively communicates statistical and technical ideas and results to non-technical stakeholders in written and verbal form to ensure decision points and their impact are clearly understood by all audiences
• Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies.  Tracks and reports progress.  Keeps stakeholders apprised of project status and implications for completion.
• Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication.
• Mentor other analysts on how to a) determine appropriate statistical analysis methods, b) leverage appropriate programing languages and tools, and c) generate and interpret statistical analysis outputs.
• Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.
• Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.
• Works closely with IT on the ongoing improvement of Mount Sinai’s integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.
• Demonstrates advanced level proficiency with the principles and methodologies of process improvement. Applies these in the execution of responsibilities in support of a process focused approach.
• Other duties as assigned.

• Master's or Ph.D. degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Information Technology, Mathematics, Physics) or equivalent practical experience
• 4+ years of work experience in data science, software engineering, or data analysis
• 2+ years of hands-on experience with Scala and Python, including documentation for reproducibility
• 2+ years of hands-on experience with database languages (e.g., SQL, NoSQL)
• Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques
• Applied experience in ML fields, such as natural language processing, computer vision, and statistical learning theory
• Experience handling terabyte-sized datasets, exploring data to discover hidden patterns, using data visualization tools, and leveraging GPUs for model development
• Proficiency in articulating technical concepts to diverse audiences, both technical and non-technical, and delivering data-driven presentations.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP)
• Experience with version control systems (e.g., Git)
• Knowledge of big data technologies (e.g., Hadoop, Spark)
• Self-motivated with a demonstrated ability to work independently, and to exercise independent judgment in developing complex techniques or programs in a dynamic environment.

Preferred Qualifications                                                                                                      

• Publications or presentations in recognized journals or conferences
• Deep technical skills, 2+ years of experience in running active pilot and business savvy to interface with product owner and users working group
• Deep knowledge and hands-on experience in agile project management