Legal Data Analyst, Applied Data Science

Imagine what you could do here. At Apple new ideas have a way of becoming great products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could you passionate about turning complex legal data into actionable insights and leveraging AI to do it faster and smarternDo you thrive on uncovering patterns trends and anomalies that others miss using both traditional analytics and AI-powered techniquesnCan you bridge the gap between raw data AI capabilities and strategic decision-makingnnThe Applied Data Science team within Legal Operations is building the data foundation that powers AI and analytics for a global legal organization. The Legal Data Analyst role is central to this mission leveraging AI tools to accelerate analysis preparing data for AI consumption and surfacing insights that drive operational excellence.

The Legal Data Analyst delivers analytical insights and ensures data readiness for AI and analytics across Legal Operations. You will leverage AI tools to accelerate your work using AI for data profiling anomaly detection pattern recognition and insight generation. You will analyze legal operations data to uncover trends perform spend and matter analysis build forecasting models and prepare data for AI consumption. This role combines analytical rigor with AI fluency and deep understanding of legal operations to drive data-informed decisions.

Leverage AI tools and techniques to accelerate data analysis automate repetitive tasks and surface insights at scalenUse AI-assisted data profiling anomaly detection and pattern recognition to identify data quality issues and trends fasternAnalyze legal operations data to surface trends patterns and actionable insights across matters spend contracts and vendorsnDevelop spend analysis matter forecasting and resource utilization models that inform strategic decisions using AI to enhance predictive capabilitiesnProfile and assess data quality across legal systems including matter management contract management eBilling and document managementnCleanse standardize and enrich data to meet quality thresholds required for AI and analytics consumptionnValidate entity data (law firms timekeepers vendors counterparties) to support entity resolution initiativesnBuild analytical models that support rate negotiations vendor performance evaluation and outside counsel managementnPartner with AI/ML Engineers to identify opportunities where AI can automate or augment analytical workflowsnDocument data lineage business rules and transformation logicnPartner with Data Stewards across practice groups to enforce data quality at the sourcenDevelop and maintain analytical dashboards data quality reports and monitoring toolsnTranslate analytical findings into clear recommendations for practice group and leadership audiences

4 years of experience in data analysis business intelligence and analytics rolesnStrong proficiency in SQL Python and experience with analytical and data profiling toolsnExperience using AI and LLM-based tools to accelerate analytical worknExperience with statistical analysis trend analysis and forecasting techniquesnExperience working with enterprise data systems (ERP CRM matter management or similar)nStrong analytical and problem-solving skills with attention to detailnAbility to communicate analytical findings and data quality insights to technical and non-technical stakeholdersnExperience building in and presenting with BI and visualization tools (Tableau Power BI or similar)nDeriving and defining KPIs and other business impact metrics for leadership

Experience with legal operations data (matter management eBilling CLM document management)nDemonstrated ability to integrate AI tools into daily analytical workflows not just experimentation but production usenUnderstanding of prompt engineering techniques to get better results from AI toolsnUnderstanding of legal spend management LEDES/UTBMS billing codes and outside counsel metricsnExperience with predictive analytics and forecasting modelsnFamiliarity with data governance frameworks and data stewardship modelsnExperience with data quality tools (Great Expectations Monte Carlo or similar)nKnowledge of entity resolution concepts and master data managementnUnderstanding of how data quality impacts AI/ML model performancenExperience in corporate legal department or professional services environment