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About the role

You own the end to end definition of data value streams for strategic clients, translating ambiguous business questions into clear analytical roadmaps. You own the design and governance of modern data platforms that balance scalability with practical delivery timelines. You own the orchestration of advanced analytics and AI initiatives, ensuring models are deployed responsibly and generate measurable business outcomes. You own the mentorship of cross functional partners, elevating their data literacy and enabling self service experimentation. You own the continuous evaluation of tools and frameworks, selecting technologies that reduce complexity and accelerate insight. You own the articulation of technical tradeoffs to executive audiences, aligning data investments with organizational priorities. You own the stewardship of data quality and reliability, establishing standards that support trustworthy decision making across the enterprise. You own the navigation of evolving market trends, identifying opportunities where data and automation can redefine competitive advantage for our clients.

Key facts

What you'll do

Define and lead the discovery phase for data and AI initiatives, aligning stakeholder expectations with feasible technical solutions.

Architect scalable data platforms that integrate structured and unstructured sources while enforcing governance, security, and compliance standards.

Quantify business impact by designing experiments and key performance indicators that demonstrate the value of analytics and automation investments.

Develop and deploy predictive models and machine learning workflows that are robust, interpretable, and maintainable in production environments.

Champion data quality and lineage practices, ensuring that insights are based on accurate, consistent, and well documented information.

Partner with product and operations leaders to embed analytics into daily workflows, driving adoption through intuitive visualizations and clear narratives.

Evaluate emerging technologies and vendor solutions, recommending strategies that balance innovation with risk, cost, and operational simplicity.

Mentor analysts and data practitioners, fostering a culture of rigorous inquiry, experimentation, and continuous learning across teams.

Coordinate roadmaps that balance quick wins with long term platform investments, managing dependencies and resource constraints effectively.

Translate complex analytical concepts into actionable recommendations for non technical audiences, supporting decision making at all levels.

Lead cross functional collaboration, aligning data, engineering, and business teams around shared objectives and success metrics.

Champion ethical AI principles, ensuring that models are fair, transparent, and aligned with organizational values and regulatory expectations.

Drive the documentation and communication of methodologies, enabling reproducibility and knowledge transfer across engagements.

Requirements

You possess a bachelor's degree in a quantitative field or equivalent practical experience, demonstrating a strong foundation in analytics, mathematics, or computer science.

You bring a minimum of eight years of professional experience in data, analytics, or technology roles, with a proven track record of delivering complex projects.

You have hands on experience with modern data platforms, including databases, data warehouses, and data lake architectures, along with ETL and ELT processes.

You are proficient in at least one programming language commonly used for data science and analytics, such as Python or R, and you write clean, maintainable, and tested code.

You have practical experience building and deploying machine learning models, understanding model lifecycle management, performance monitoring, and retraining strategies.

You understand data governance, security, and compliance frameworks, including how to implement access controls, auditing, and data privacy practices.

You communicate effectively with both technical and non technical stakeholders, articulating tradeoffs and justifying recommendations based on evidence.

You are comfortable working in a fast paced, ambiguous environment, managing multiple priorities while maintaining attention to detail and high quality standards.

Nice to have

Experience with cloud platforms and managed services for data and AI, such as those provided by major hyperscalers.

Knowledge of MLOps practices and tooling that support model deployment, monitoring, and operationalization at scale.

Familiarity with data visualization tools and dashboarding frameworks, enabling rapid exploration and clear storytelling.

Background in industries subject to heavy regulation, where data privacy, auditability, and compliance are critical success factors.

Practical notes

This is a full time position based in Chicago, Illinois.

Travel may be required as part of client engagements, typically up to 25 percent of the time.

Candidates must be authorized to work in the United States without sponsorship for this role at this time.

The listed compensation reflects target ranges based on candidate qualifications and relevant experience.