Director, Data Science Machine Learning - Healthcare Analytics Solutions

Overview

Healthcare Analytics Solutions (HAS) is an innovative team within Quest Diagnostics that leverages Quest data to develop products and services to solve the challenges and improve outcomes in healthcare across many different markets (Pharma, Clinical Trials, Health Plans/Payers, Hospitals/Health Systems, and Public Health agencies).

The Director, Data Science Machine Learning is responsible for leading and managing innovation and implementation of advanced analytics solutions to complex challenges to improve the overall impact and value of diagnostic testing and patient health information and services that patients and doctors need to make better healthcare decisions.  In this role, you will research and explore novel approaches to complex challenges and help design, develop, and deploy innovative solutions that use the spectrum of data science fields of study, including natural language processing, machine learning and AI technology, to improve patient healthcare outcomes.  You will be a hands-on leader overseeing a team of highly skilled data scientists and will coordinate and collaborate across Quest Technology and other business partners ensuring synchronicity of data science solutions, application development, and alignment with business needs and strategy.

Responsibilities

• Hands-on technology leader who can (and will) get your hands dirty in the data and AI/ML development activities.
• Lead a team of data scientists and provide coaching and mentorship to build a positive and collaborative culture within our workplace and foster the professional growth of our staff. 
• Coordinate and collaborate with Quest Technology and Quest business units (including data scientists embedded in the business units) in assessing the current and future data science needs of the organization, and translate this understanding into practical, stable, innovative recommendations to facilitate strategic solutions and help drive innovation.
• Manage the portfolio of requirements for your team and coordinate team activities with other technology teams and business customers.
• Promote and influence the development and introduction of industry standards in development of AI/ML solutions; consistently define and apply technologies, standards, and data analytics practices.
• Test and ensure data science solutions yield high-quality, high-confidence results in accordance with Quest’s quality standards and expectations of excellence in delivery of client services and solutions.
• Act as a trusted technical advisor to business customers and solve complex data challenges.
• Develop algorithms and processes to transform data into useful, actionable information.
• Support and enable the development of Business Intelligence and Data Science solutions.
• Collaborate with management to understand technology and company strategies.
• Collaborate with other software and data engineers to solve and bring new perspectives to complex problems.
• Collaborate with architecture and lead engineers to ensure consistent development practices.
• Ensure compliance with data governance and security policies.
• Embrace new technologies and an ever-changing environment.
• Perform and support unit and integration testing.
• Drive improvements in people, processes, and technology.

Qualifications

• 12+ years of advanced data analytics, data science, and AI/ML development experience.
• 6+ years of technical leadership experience including experience leading data science solutions from design to operational deployment.
• Demonstrable experience leading multiple data science teams and projects at the same time.
• Experience working with agile software development methods, such as Scrum and Kanban (Agile certification preferred).
• Expert knowledge and experience in developing analytics solutions in a cloud environment using modern data science tools, programming languages, and libraries (AWS, Azure, or GCP Cloud certification preferred).
• Expert knowledge of advanced analytics concepts and methodologies.
• Experience with the Machine Learning Life Cycle with demonstrable experience having taken advanced analytics and machine learning projects from problem formulation to research and exploration to development and successful deployment.
• Experience with time series data leveraging methods such as regression, classification, survival analysis.
• Experience with Deep Learning and associated tools, such as TensorFlow and GPUs.
• Must have excellent executive presence and business acumen to deliver complex analytics concepts and insights to a non-technical business audience.
• Experience with the cloud (AWS, Azure and/or Google Cloud Platform)
• Experience in cloud-based data warehouses (Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse Analytics).
• Experience with cloud-based ETL/ELT tools (Matillion, Glue, Data Factory) and data modeling.
• Experience in deep learning and neural networks, including Convolutional Neural Networks and Recurrent Neural Networks preferred.
• Exposure to version control systems (Git, SVN).

Skill Sets and Attributes:

• Understanding of and willingness to embrace Agile Principles (Scrum).
• Open mindset, ability to quickly adapt new technologies and learn new practice.
• Healthcare industry knowledge is preferred.
• Knowledge of data science solution design including applying careful consideration of what is desired from data science results, how to define expected value as a key evaluation framework, and consideration of appropriate comparative baselines.
• Knowledge of statistical methods, including multivariate regression, Bayesian statistics, and time-series analysis.
• Knowledge of supervised and unsupervised machine learning methods.
• Knowledge of natural language processing and transformer-based machine learning techniques (e.g., BERT).
• Knowledge of dimensionality reduction techniques and regularization techniques (e.g., ridge regression and lasso).
• Demonstrated knowledge of Python, R, Julia, Scala, C++, Java and/or other modern data and analytics programming languages.
• Demonstrated knowledge of operating systems (macOS, Microsoft Windows, Linux, Solaris and/or UNIX).

Educational Requirements:

• A Master’s degree in a technology-related field of study is required. A PhD is preferred.
• Agile Certification and/or Project Management Certification is preferred
• Certifications in data science or analytics (CAP, AWS Machine Learning) and/or cloud solutions such as AWS, Snowflake, Matillion will help evidence applicant knowledge of core solutions used across Quest’s enterprise data ecosystem.

EEO

Equal Opportunity Employer: Race/Color/Sex/Sexual Orientation/Gender Identity/Religion/National Origin/Disability/Vets