Data Analytics Manager - Client Legal Services

Key Responsibilities
Analytics Strategy & Leadership: Define and execute the CLS Legal Operations data and analytics roadmap, aligning priorities to operational strategy, litigation outcomes, cost management, quality, and leadership decision needs.
Power BI Product Ownership: Lead the design, development, governance, and lifecycle management of executive and operational Power BI dashboards, semantic models, KPIs, and self-service reporting experiences.
Microsoft Fabric & Data Engineering: Partner with Legal Technology, ATS, and source-system owners to build and sustain governed Fabric pipelines, lakehouse or warehouse solutions, reusable data products, and reliable integrations from TeamConnect and other core systems.
AI Integration: Identify and implement responsible AI use cases across analytics and Legal Operations, including natural-language insights, intelligent summarization, anomaly detection, workflow support, and decision-assistance capabilities with appropriate governance and human oversight.
Predictive Modeling: Establish the foundation for predictive and prescriptive analytics, including use-case selection, feature and model development, validation, monitoring, and translation of model outputs into actionable operational and litigation insights.
ROI & Value Realization: Create consistent business cases and measurement frameworks that connect volume, time savings, capacity, cost avoidance, spend reduction, quality improvement, and business outcomes to technology and process investments.
Data Governance & Quality: Establish standards for data definitions, KPI governance, lineage, access, quality controls, reconciliation, documentation, and issue resolution to strengthen trust in reporting.
Legal Operations Insight: Provide analytical support for assignment effectiveness, staffing and capacity, cycle time, task compliance, service delivery, quality, litigation trends, outside counsel performance, and workflow optimization.
Executive Storytelling: Translate complex data and technical concepts into concise, decision-ready insights and recommendations for CLS and Law & Regulation leadership.
Team Leadership & Capability Building: Coach and develop analysts, clarify roles and operating practices, document institutional knowledge, strengthen technical skills, and build sustainable bench strength for long-term continuity.
Cross-Functional Partnership: Collaborate with Legal, Claims, Finance, Quality, Business Architecture, Legal Technology, and enterprise data teams to prioritize solutions, prevent duplication, and accelerate adoption.
Innovation & Continuous Improvement: Monitor emerging analytics, AI, and legal technology capabilities; test high-value use cases; and move successful solutions from prototype to governed production use.

Capabilities & Technical Proficiency

Advanced Power BI expertise, including data modeling, semantic models, DAX, Power Query, visualization standards, performance optimization, deployment, security, and governance.
Working knowledge of Microsoft Fabric, including OneLake, data pipelines, notebooks, lakehouse or warehouse patterns, data engineering, governance, and integration with Power BI.
Experience applying Python, SQL, machine learning, or comparable analytical methods to forecasting, classification, segmentation, anomaly detection, and predictive modeling.
Practical understanding of generative AI, copilots, data agents, prompt-driven analytics, responsible AI controls, and human-in-the-loop design.
Strong financial and operational acumen, including cost-benefit analysis, capacity modeling, unit cost, benefits tracking, and ROI realization.
Experience establishing data quality controls, KPI definitions, documentation, testing, change management, and production support practices.
Ability to lead through influence across technical and business teams and communicate effectively with senior leaders.

Preferred Experience

7 or more years of progressive experience in data analytics, business intelligence, data engineering, advanced analytics, or a related discipline.
Experience leading analysts or multidisciplinary analytics teams and developing technical talent.
Demonstrated ownership of enterprise reporting products or analytics platforms from intake and design through deployment, adoption, and support.
Experience in Legal Operations, insurance, claims, litigation, finance, or another complex regulated environment is strongly preferred.
Bachelors degree in analytics, data science, computer science, information systems, finance, business, or a related field preferred; an equivalent combination of education and experience may be considered.