Data Scientist III-Psychiatry

Mount Sinai Health System•New York, NY

About The Position

As a Data Scientist 3, play a pivotal role in shaping the direction of machine learning projects. they will lead a team of talented data scientists, guiding them in designing, developing, and deploying complex machine learning applications. Their expertise will be crucial in solving challenging development and operational problems and contributing to the team growth.

Requirements

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
7+ years of work experience in software development, machine Learning, and data management
5+ years of hands-on experience in analytic system and machine learning applications
3+ years of hands-on experience in data-driven product design and project planning
4+ Publications or presentations in recognized journals or conferences
Mentoring 4+ junior data scientists or data science interns
Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques
Solid experience in ML fields, such as natural language processing, computer vision, and statistical learning theory
Proficiency in articulating technical concepts to diverse audiences, both technical and non-technical, and delivering data-driven presentations.
Solid experience with cloud computing platforms (e.g., AWS, Azure, GCP)
Deep knowledge and hands-on experience in agile project management
Exceptional problem-solving skills and the ability to communicate technical concepts effectively

Responsibilities

Lead and mentor a team of data scientists and machine learning engineers, fostering a collaborative and innovative work environment
Drive the design, development, and optimization of advanced machine learning applications to address complex business challenges
Lead data mining and management procedures
Ensure data quality and integrity in product development and deployment
Interpret and analyze data problems
Plan, prioritize, and manage ML projects lead machine learning product development and implementation
Monitor performance of data-driven products
Design and lead proof of concepts (POCs) to investigate new technologies in machine learning and AI
Stay at the forefront of machine learning advancements and lead the implementation of novel algorithms and techniques
Play a key role in defining the machine learning strategy for the organization and align it with operational goals
Engage in different initiatives and collaborate with stakeholders to understand and address operational needs through machine learning solutions
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.