Lead Data Scientist

Vizient•Chicago, IL

About The Position

In this role, you will develop automated analytics products and conduct sophisticated data analysis to address critical business and client questions. You will design, implement, and deploy advanced data science solutions across multiple domains, translating complex findings into actionable insights that improve clinical, operational, and economic outcomes. You will guide data scientists, lead the design of predictive, machine learning, and generative AI approaches, and ensure high-quality, scalable analytic solutions that support organizational objectives.

Requirements

Relevant degree preferred. Advanced degree in applied mathematics, statistics, computer science, econometrics, or a related field is a plus.
7 or more years of relevant experience required.
Proven ability to apply advanced modeling, forecasting, anomaly detection, and natural language processing required.
Demonstrated advanced knowledge of data science methodologies, statistical modeling, machine learning, and generative AI techniques required.
Strong understanding of Natural Language Processing (NLP) techniques, including text classification, sentiment analysis, information extraction, and Large Language Model (LLM)-based approaches required.
Expertise in programming languages such as Python, R, SAS, SQL, or similar tools required.
Knowledge of responsible AI principles, including model explainability, bias detection, fairness assessment, and ethical use of data.
Experience deploying, monitoring, and maintaining machine learning and generative AI models in production environments.
Experience implementing model governance practices such as documentation standards, version control, validation protocols, and audit readiness.
Experience working with cloud-based and distributed data platforms and modern analytics frameworks such as Databricks.
Strong analytical, problem-solving, communication, and presentation skills with the ability to convey complex concepts to non-technical audiences.
Experience guiding or mentoring data scientists.

Responsibilities

Lead the design and implementation of advanced machine learning, generative AI, statistical modeling, and unsupervised learning approaches across structured and unstructured data.
Build and deploy scalable, automated data science products and reusable analytic assets across multiple projects and domains.
Analyze large-scale, high-dimensional datasets using Python, R, SQL, and distributed computing platforms to identify trends and actionable insights.
Apply deep expertise across end-to-end data science workflows, including data discovery, feature engineering, validation, and insight publishing.
Translate complex analytical outputs into clear dashboards, reports, and presentations for technical and non-technical audiences.
Make key analytic and architectural design decisions, define project goals based on strategic business needs, and own final solution outcomes.
Apply expert-level proficiency in programming languages and advanced analytics platforms, including cloud-based and distributed frameworks.
Lead code development and reviews, establish best practices, and mentor data scientists in advanced modeling and responsible AI usage.
Evaluate and adopt emerging tools, advanced frameworks, and generative AI technologies to continuously enhance analytical capabilities and workflows.
Partner with engineering and platform teams to support production deployment, monitoring, and lifecycle management of machine learning and generative AI models.
Implement responsible AI and model governance practices, including documentation, explainability, bias assessment, and validation standards.
Collaborate with cross-functional teams to integrate advanced analytics and AI solutions into products, workflows, and business processes.
Apply a solutions-oriented mindset to complex, multi-project initiatives and make autonomous decisions on data science deliverables aligned with enterprise objectives.