AVP, Machine Learning & Modeling
At a glance
Mid-level Machine Learning Engineering role at Vizient. Irving · full-time · $156,500–$290,100 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Set the machine learning direction and build a roadmap tied to corporate goals and emerging AI, prediction and optimization work
- Guide model creation and testing for forecasting, risk, operational efficiency and client performance, with attention to accuracy and ethical use
- Put model documentation, version tracking, validation and performance checks in place, working with risk and compliance teams
- Lead and mentor data scientists, ML engineers and quantitative analysts, keeping projects aligned with business needs and timelines
- Find data science opportunities with business, IT and analytics leaders, then explain results for executive decisions
What you bring
- A degree in a quantitative field such as data science, statistics or computer science is preferred
- Expertise in machine learning, deep learning and statistical modeling, plus strong Python, SQL and cloud AI/ML platform skills
- Knowledge of ML Ops, model governance and lifecycle practices
- A track record leading data science teams in a large, matrixed organization and translating business problems into measurable analytical outcomes
Who this fits
This role suits a senior technical leader who can oversee a multidisciplinary team and present complex findings to nontechnical audiences. Familiarity with healthcare, financial or operational analytics is also relevant.
From the employer
When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.
In this role, you will lead the design, development, and implementation of advanced analytics, statistical modeling, and artificial intelligence solutions to drive data-informed decision-making across the enterprise. Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable solutions that support strategic business objectives, operational excellence, and client value creation. Serve as a key thought leader, guiding the organization’s data science strategy, ensuring model governance and compliance, and advancing the use of cutting-edge machine learning methodologies.
Role Responsibilities:
Strategic Leadership and Vision
Provide strategic direction for the organization’s machine learning and modeling initiatives. Develop and execute a roadmap for data-driven innovation aligned with corporate goals and emerging technologies in AI, predictive analytics, and optimization.
Model Development and Deployment
Oversee the design, development, and validation of statistical, econometric, and machine learning models that support forecasting, risk assessment, operational efficiency, and client performance improvement. Ensure model accuracy, interpretability, and ethical use of data.
Model Governance and Compliance
Establish and maintain robust model governance frameworks, including documentation, version control, validation, and ongoing performance monitoring. Partner with risk management and compliance teams to ensure adherence to regulatory and ethical standards.
Team Development and Leadership
Lead and mentor a multidisciplinary team of data scientists, ML engineers, and quantitative analysts. Foster a culture of innovation, continuous learning, and collaboration while ensuring alignment with business priorities and project timelines.
Cross-Functional Collaboration
Collaborate with business leaders, IT, and analytics stakeholders to identify opportunities for data science applications that drive measurable business outcomes. Translate complex analytical results into actionable insights for executive decision-making.
Research and Innovation
Stay at the forefront of emerging AI and machine learning technologies. Evaluate and integrate new tools, frameworks, and methodologies to enhance model performance and scalability. Promote experimentation and best practices in applied data science.
Requirements:
- Bachelors or Masters or Doctorate degree in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, Economics, or a related quantitative field preferred
- Expertise in machine learning, deep learning, and statistical modeling techniques (e.g., regression, time series, NLP, ensemble methods, neural networks).
- Strong proficiency in Python, SQL, and with cloud-based AI/ML platforms (AWS SageMaker, Azure ML, Databricks, etc.)
- Knowledge of ML Ops, model governance, and lifecycle management best practices.
- Demonstrated ability to translate business problems into analytical frameworks and deliver measurable outcomes.
- Excellent leadership, communication, and stakeholder management skills, with the ability to present complex findings to non-technical audiences.
- Proven experience building and leading high-performing data science teams in a large, matrixed organization.
- Familiarity with healthcare, financial, or operational analytics.
Estimated Hiring Range:
At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $156,500.00 to $290,100.00.This position is also incentive eligible.
Vizient has a comprehensive benefits plan! Please view our benefits here:
http://www.vizientinc.com/about-us/careers
Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities
The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.