Masters Data Science Jobs in Chicago, IL (NOW HIRING)

About Kirkland & Ellis
At Kirkland & Ellis, we don't just meet the standard for legal excellence - we set it. Our culture is built on teamwork, ingenuity and an unwavering commitment to continuous growth. We tackle the most sophisticated legal challenges with bold ideas and innovative solutions, powered by the exceptional experience and ambition of our 7,000+ people, including 4,000+ attorneys, across 24 offices worldwide. Our dedicated professionals share our lawyers' commitment to excellence and show up each day to do meaningful work that helps drive global business, investment and innovation forward.
What You'll Do
Are you a strategic data leader who can transform enterprise information into a competitive advantage?
As the Director of Enterprise Data and Analytics, you will lead the vision, strategy, and execution of the firm's enterprise data capabilities, ensuring data is treated as a critical business asset. In this high-impact leadership role, you will partner with firm leadership, practice groups, and business services teams to build a data-driven culture that enables smarter decision-making, operational excellence, innovation, and growth.
You will oversee the full data ecosystem-from architecture and governance to analytics, reporting, artificial intelligence (AI) readiness, and data quality-while ensuring the highest standards of security, privacy, and regulatory compliance.
Enterprise Data Strategy: Develop and execute a firm-wide data strategy aligned with business priorities, translating organizational goals into actionable roadmaps with measurable outcomes.
Business Partnership & Influence: Collaborate with executive leaders and stakeholders to secure investment in data initiatives by demonstrating business value through efficiency gains, risk reduction, revenue enablement, and competitive differentiation.
Data Architecture Leadership: Define and evolve enterprise data architecture, including cloud platforms, data lakehouse environments, integration frameworks, data models, and technology standards that support future growth in analytics and AI.
Technology Evaluation & Governance: Lead the assessment, selection, and implementation of data platforms and tools while ensuring alignment with enterprise technology, security, and vendor management standards.
Data Governance Enablement: Establish and operationalize a comprehensive governance framework covering data ownership, stewardship, metadata management, lineage, master data management, and enterprise standards.
Data Quality Management: Build and oversee processes that ensure data integrity, accuracy, consistency, completeness, and timeliness through monitoring, remediation, and continuous improvement programs.
Integration Strategy & Delivery: Direct integration architecture and enterprise data movement across core business systems, leveraging Application Programming Interfaces (APIs), Extract, Transform, Load/Extract, Load, Transform (ETL/ELT), streaming technologies, and modern integration patterns.
Pipeline Development: Lead the design, development, and lifecycle management of scalable data pipelines using Microsoft Azure and Microsoft Fabric technologies to support reporting, analytics, and AI solutions.
AI Data Readiness: Prepare the organization's data landscape for AI and machine learning initiatives, including high-quality training data, Retrieval-Augmented Generation (RAG), GraphRAG, feature engineering, and responsible AI practices.
Risk & Compliance Oversight: Advise leadership on data-related risks associated with generative AI, client confidentiality, intellectual property protection, data privacy, and regulatory obligations.
Reporting & Analytics Excellence: Own enterprise reporting and dashboard capabilities, establishing standards and service levels for operational, financial, and management reporting through Microsoft Fabric, Microsoft Power BI, and Azure analytics services.
Data Science Enablement: Support advanced analytics and data science initiatives by providing strategic direction, methodologies, and resources that deliver meaningful business outcomes.
Team Leadership & Culture: Build, mentor, and lead high-performing teams across data engineering, analytics, reporting, governance, integration, and data science while fostering a data-driven culture throughout the organization.
What You'll Bring
Education & Credentials: Bachelor's degree in computer science, Data Science, Information Systems, Statistics, Business Administration, or a related field required. Master's degree or Master of Business Administration (MBA) strongly preferred. Certifications such as Certified Data Management Professional (CDMP), Data Management Association (DAMA), or The Open Group Architecture Framework (TOGAF) are a plus.
Leadership Experience: 10+ years of progressive experience in data management, architecture, engineering, or analytics, including at least 3 years leading enterprise data functions at the Director level or equivalent.
Strategic Impact: Demonstrated success developing and executing enterprise data strategies that delivered measurable business outcomes, including revenue growth, operational improvements, cost reduction, or risk mitigation.
Technical Expertise: Deep knowledge of Microsoft Fabric, Azure Data Factory, Azure Synapse Analytics, Databricks, Azure Data Lake Storage, Power BI, data lake and lakehouse architectures, data modeling, enterprise integrations, and modern data engineering practices.
Governance & Data Management: Strong expertise in data governance frameworks, metadata management, data cataloging, stewardship models, data quality programs, and regulatory compliance requirements.
AI & Advanced Analytics: Hands-on experience preparing enterprise data environments for AI and machine learning workloads, including RAG architectures, feature engineering, responsible AI practices, predictive analytics, and data science enablement.
People Leadership: Proven ability to lead, develop, and inspire multidisciplinary teams while driving accountability, collaboration, innovation, and continuous improvement.
Executive Communication: Exceptional communication and stakeholder management skills, with the ability to translate complex technical concepts into clear business value for senior leaders.
Change Leadership: Experience building organizational adoption of data-driven decision-making and leading large-scale transformation initiatives across technical and business teams.
Industry Knowledge: Experience within professional services, legal, financial services, or other highly regulated environments is preferred.
Vendor & Technology Management: Strong background evaluating, selecting, and managing technology vendors, platforms, and strategic partnerships.
Mobility: Ability to travel as needed.
If you're excited to shape enterprise data strategy, enable AI innovation, and lead transformative analytics capabilities as a Director of Enterprise Data and Analytics, we'd love to hear from you!
Compensation
The base salary range below represents the low and high end of the salary range for this position in Chicago. This range may differ based on your geographic location and cost of living considerations. At Kirkland & Ellis, we consider compensation more than just a base salary. We offer an exceptional range of flexible benefits including comprehensive healthcare, paid time off, and retirement. We also offer personal support and tailored learning and development opportunities all designed to help you realize your full potential both in life and at work.
Compensation Range:
Chicago: $310,000 - $375,000
How to Apply
Thank you for your interest in Kirkland & Ellis LLP. To complete an application and submit your resume, please click "Apply Now."
Don't meet every job requirement? That's okay! If you're excited about this role but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others at Kirkland.
Equal Employment Opportunity
All employment decisions, including the recruiting, hiring, placement, training availability, promotion, compensation, evaluation, disciplinary actions, and termination of employment (if necessary) are made without regard to the employee's race, color, creed, religion, sex, pregnancy or childbirth, personal appearance, family responsibilities, sexual orientation or preference, gender identity, political affiliation, source of income, place of residence, national or ethnic origin, ancestry, age, marital status, military veteran status, unfavorable discharge from military service, physical or mental disability, or on any other basis prohibited by applicable law. #LI-Hybrid #LI-LC1