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AVP, Machine Learning & Modeling

Vizient · Chicago, IL · $156,500–$290,100 a year · Full time

Posted Aug 17, 2026 · We last checked this listing on Oct 5, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a model your team built that performed well offline but disappointed in production. What happened?

What they are checking: Whether they understand drift, data leakage and deployment gaps from real experience.

Tell me about how you developed a strong data scientist into a leader.

What they are checking: Whether they invest in growing people, not just delivering projects.

What would you do

A business leader wants a predictive model, but the data quality is poor. What do you tell them?

What they are checking: Whether they can be honest about data limits and offer a realistic path instead of overpromising.

About the work

How would you build a roadmap for machine learning and modeling that ties directly to business goals rather than interesting technical problems?

What they are checking: Whether they can steer data science toward measurable enterprise value.

What does good model governance look like in a company working with healthcare data?

What they are checking: Whether they understand validation, documentation, monitoring and compliance for models in a regulated space.

How do you organize a team of data scientists, modelers and ML engineers so work actually reaches production?

What they are checking: Whether they can structure roles and handoffs to avoid models that never get deployed.

How do you decide between a simple statistical model and a complex machine learning approach?

What they are checking: Whether they value interpretability and fit-for-purpose over sophistication for its own sake.

How do you check models for bias, especially when outputs could affect clinical or operational decisions at hospitals?

What they are checking: Whether they take fairness seriously and have concrete methods for testing it.

How would you explain a model's results and limits to non-technical executives?

What they are checking: Whether they can build trust in models by communicating uncertainty clearly.

Where do you see optimization or generative AI fitting alongside traditional predictive modeling here?

What they are checking: Whether they can place newer methods sensibly within a broader analytics strategy.

Practice this interview out loud.

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The full job description

As published by Vizient.

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.

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