Overview
On Site
Full Time
Skills
Reporting
Advanced analytics
Predictive analytics
Centricity
Strategy
FOCUS
Generative Artificial Intelligence (AI)
Governance
Strategic leadership
Customer experience
Software development
Organizational skills
Training
Design
Use cases
Mentorship
Coaching
Professional development
Computer science
Statistics
Mathematics
Economics
Management
Predictive modelling
Artificial intelligence
Python
PySpark
Keras
TensorFlow
Collaboration
Analytics
Data Science
Analytical skill
Regression analysis
Algorithms
Neural Network
Software engineering
Version control
Continuous integration
Continuous delivery
Microsoft Azure
Google Cloud
Google Cloud Platform
Data warehouse
Cloud computing
Snow flake schema
Databricks
Marketing
Health care
Machine Learning (ML)
Deep learning
Problem solving
ROOT
Communication
Leadership
Natural language processing
Streaming
Data
Design of experiments
A/B testing
Forecasting
Time series
Data cleansing
Modeling
Optimization
Software deployment
Workflow
Agile
Job Details
JOB SUMMARY
Reporting to the SVP of Analytics and Intelligence, the Director of Strategic Advanced Analytics - AI/ML, will lead a team of data scientists to build out advanced predictive analytics capabilities and a team of data scientists to mature support for our customer centricity strategy. The focus of this position is on building LLM and GenAI capabilities across multiple domains, employing a mix of traditional AI/ML and Gen AI. The leader will work closely with key business stakeholders to develop use cases related to difficult to solve and complex business challenges, build machine learning models where they will identify key data features that will enable the models to derive insights that are predictive in nature and enable stakeholders to take action to improve business outcomes. This leader will also participate in the GenAI Working Team, a cross-functional / discipline team to establish governance and learn from other organizations.
ROLES & RESPONSIBILITIES
Provide strategic leadership to advance the organization's analytics maturity by demonstrating new capabilities enabled by Artificial Intelligence/Machine Learning
Evolve the CoE model to scale AI/ML capabilities across BSWH
Work collaboratively with executive leaders in different domains of data to define, measure, develop, and deliver impactful analytics products and solutions that drive actionable insights and measurable business value
Lead team to deliver improved health system outcomes (improved customer experience, satisfaction, loyalty, retention, quality, safety, and limit non-beneficial clinical variation, etc.) by leveraging advanced data science and engineering approaches
Lead team to design machine learning systems using programming skills, which involves assessing and organizing large datasets, training models and executing tests/experiments to automate model optimization
Collaborate closely with business and IT stakeholders to thoroughly understand current business functional processes and requirements
Lead team to determine the appropriate analytical technique and create model(s)to generate the insight required as defined by the requirements of the use case, in some cases
Ensure team is focused on ability to Iterate and improve the predictability and explain-ability of complex AI/ML models
Lead team to design methods and frameworks that ensure data science tools and techniques used are consistent across teams, scalable, and efficient
Maintain expertise and awareness of emerging data science techniques, technologies, and potential business applications for AI/ML
Collaboratively work with data platform team in designing and building cloud-based infrastructure to facilitate analytics and experimentation
Lead team to build and maintain a robust library of data science solutions, reusable templates, models, algorithms, neural networks, and supporting code
Working in a consultative manner, manage multiple executive stakeholder relationships effectively, curating use cases and data features
Partner inside and outside the organization for success
Lead and develop more junior data scientists, providing mentorship, coaching, and guidance for professional development
Perform other position-appropriate duties as required in a competent, professional, and courteous manner
REQUIRED EXPERIENCE
Master's degree in a quantitative field like data science, computer science, engineering, statistics, mathematics, economics, or related field or significant, demonstrated experience in the role.
Experience leading and growing leveraged teams of data scientists in managing multiple concurrent, complex, and scaled data science projects
9+ years of hands-on data scientist mathematical predictive modeling experience in a business environment or equivalent
Proficiency in common language / tools for AI/ML - (e.g. Python/Pyspark, Keras, Tensorflow libraries, etc.)
Experience working in a cloud environment such as Azure, and their ML services and tooling
Solid interpersonal skills, such as great communication and collaboration, due to the high-level interaction with other analytics and intelligence teams, as well as cross functional teams
Experience investigating and implementing cutting edge data science methodologies, technologies, and platforms in a large-scale and complex organizations
Familiarity with developing complex algorithms associated with advanced analytic topics, including binary classification algorithms, regression algorithms, Neural Network frameworks, and Natural Language Processing
Demonstrated and comprehensive knowledge and understanding of software engineering topics, including classes, functions, version control, CI/CD, and unit tests
Technical expertise with multiple cloud compute environments - e.g. Azure, Google Cloud Platform, etc.
Experience working in EDW cloud technologies - e.g. Snowflake, DataBricks, etc.
Experience in consumer/marketing and / or healthcare (clinical or payor / ACO)
PREFERRED EXPERIENCE
PhD in above mentioned technical field
Advanced knowledge of statistical and machine learning techniques (deep learning, boosted trees, reinforcement learning, etc.)
Intellectual curiosity along with excellent problem-solving and quantitative skills including the ability to disaggregate issues, identify root causes, and recommend solutions
Strong interpersonal and communication skills in addition to technical skillset. Ability to build strong relationships, work within and lead teams, and translate technical concepts simply for non-technical stakeholders
NLP, Text, speech, streaming data
Experimental design and A/B testing
Forecasting, time-series, prediction, recommendation...
Data cleansing, feature creation, feature selection, value imputation
Prescriptive modeling, simulation, optimization
Deployment of predictions/recommendation models
Workflow skills/tools (agile, code control, etc.)
BENEFITS
Our competitive benefits package includes the following
- Immediate eligibility for health and welfare benefits
- 401(k) savings plan with dollar-for-dollar match up to 5%
- Tuition Reimbursement
- PTO accrual beginning Day 1
Note: Benefits may vary based upon position type and/or level
QUALIFICATIONS
- EDUCATION - Bachelor's
- EXPERIENCE - 5 Years of Experience
Reporting to the SVP of Analytics and Intelligence, the Director of Strategic Advanced Analytics - AI/ML, will lead a team of data scientists to build out advanced predictive analytics capabilities and a team of data scientists to mature support for our customer centricity strategy. The focus of this position is on building LLM and GenAI capabilities across multiple domains, employing a mix of traditional AI/ML and Gen AI. The leader will work closely with key business stakeholders to develop use cases related to difficult to solve and complex business challenges, build machine learning models where they will identify key data features that will enable the models to derive insights that are predictive in nature and enable stakeholders to take action to improve business outcomes. This leader will also participate in the GenAI Working Team, a cross-functional / discipline team to establish governance and learn from other organizations.
ROLES & RESPONSIBILITIES
Provide strategic leadership to advance the organization's analytics maturity by demonstrating new capabilities enabled by Artificial Intelligence/Machine Learning
Evolve the CoE model to scale AI/ML capabilities across BSWH
Work collaboratively with executive leaders in different domains of data to define, measure, develop, and deliver impactful analytics products and solutions that drive actionable insights and measurable business value
Lead team to deliver improved health system outcomes (improved customer experience, satisfaction, loyalty, retention, quality, safety, and limit non-beneficial clinical variation, etc.) by leveraging advanced data science and engineering approaches
Lead team to design machine learning systems using programming skills, which involves assessing and organizing large datasets, training models and executing tests/experiments to automate model optimization
Collaborate closely with business and IT stakeholders to thoroughly understand current business functional processes and requirements
Lead team to determine the appropriate analytical technique and create model(s)to generate the insight required as defined by the requirements of the use case, in some cases
Ensure team is focused on ability to Iterate and improve the predictability and explain-ability of complex AI/ML models
Lead team to design methods and frameworks that ensure data science tools and techniques used are consistent across teams, scalable, and efficient
Maintain expertise and awareness of emerging data science techniques, technologies, and potential business applications for AI/ML
Collaboratively work with data platform team in designing and building cloud-based infrastructure to facilitate analytics and experimentation
Lead team to build and maintain a robust library of data science solutions, reusable templates, models, algorithms, neural networks, and supporting code
Working in a consultative manner, manage multiple executive stakeholder relationships effectively, curating use cases and data features
Partner inside and outside the organization for success
Lead and develop more junior data scientists, providing mentorship, coaching, and guidance for professional development
Perform other position-appropriate duties as required in a competent, professional, and courteous manner
REQUIRED EXPERIENCE
Master's degree in a quantitative field like data science, computer science, engineering, statistics, mathematics, economics, or related field or significant, demonstrated experience in the role.
Experience leading and growing leveraged teams of data scientists in managing multiple concurrent, complex, and scaled data science projects
9+ years of hands-on data scientist mathematical predictive modeling experience in a business environment or equivalent
Proficiency in common language / tools for AI/ML - (e.g. Python/Pyspark, Keras, Tensorflow libraries, etc.)
Experience working in a cloud environment such as Azure, and their ML services and tooling
Solid interpersonal skills, such as great communication and collaboration, due to the high-level interaction with other analytics and intelligence teams, as well as cross functional teams
Experience investigating and implementing cutting edge data science methodologies, technologies, and platforms in a large-scale and complex organizations
Familiarity with developing complex algorithms associated with advanced analytic topics, including binary classification algorithms, regression algorithms, Neural Network frameworks, and Natural Language Processing
Demonstrated and comprehensive knowledge and understanding of software engineering topics, including classes, functions, version control, CI/CD, and unit tests
Technical expertise with multiple cloud compute environments - e.g. Azure, Google Cloud Platform, etc.
Experience working in EDW cloud technologies - e.g. Snowflake, DataBricks, etc.
Experience in consumer/marketing and / or healthcare (clinical or payor / ACO)
PREFERRED EXPERIENCE
PhD in above mentioned technical field
Advanced knowledge of statistical and machine learning techniques (deep learning, boosted trees, reinforcement learning, etc.)
Intellectual curiosity along with excellent problem-solving and quantitative skills including the ability to disaggregate issues, identify root causes, and recommend solutions
Strong interpersonal and communication skills in addition to technical skillset. Ability to build strong relationships, work within and lead teams, and translate technical concepts simply for non-technical stakeholders
NLP, Text, speech, streaming data
Experimental design and A/B testing
Forecasting, time-series, prediction, recommendation...
Data cleansing, feature creation, feature selection, value imputation
Prescriptive modeling, simulation, optimization
Deployment of predictions/recommendation models
Workflow skills/tools (agile, code control, etc.)
BENEFITS
Our competitive benefits package includes the following
- Immediate eligibility for health and welfare benefits
- 401(k) savings plan with dollar-for-dollar match up to 5%
- Tuition Reimbursement
- PTO accrual beginning Day 1
Note: Benefits may vary based upon position type and/or level
QUALIFICATIONS
- EDUCATION - Bachelor's
- EXPERIENCE - 5 Years of Experience
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.