• Conduct audits of client digital properties to ensure analytics, tagging, and data pipelines are correctly configured. • Design and implement analytics measurement frameworks aligned to client business, marketing, and product strategies. • Advise on and support event‑driven analytics, data layers, and tagging strategies across web, mobile, CRM, and marketing platforms. • Design and build dashboards, reports, and self‑service views using BI and visualization tools. • Troubleshoot data integrity, tracking, and pipeline issues across platforms and vendors. • Document implementations and lead enablement sessions to establish analytics best practices. • Lead stakeholder conversations to deeply understand business goals and translate them into measurement and insight requirements. • Analyze qualitative and quantitative data to inform strategic recommendations across UX, content, marketing, and product. • Develop testable hypotheses related to acquisition, engagement, conversion, retention, and experience quality. • Recommend experimentation strategies (A/B testing, personalization, SEO testing, CRO) tied to defined KPIs. • Connect insights across multiple data sources to tell a coherent, actionable story. • Identify analytics workflows that can be accelerated or augmented using AI (e.g., automated insights, anomaly detection, summarization, forecasting, and trend identification). • Leverage AI‑assisted tools to support: Data exploration and pattern discovery, Narrative generation and executive summaries, Experiment analysis and insight synthesis. • Partner with Product, Data Science, and Engineering teams to pilot AI‑enabled analytics capabilities within client engagements. • Contribute to Phase2’s evolving AI‑native delivery patterns and analytics playbooks. • Advise clients on data collection best practices in alignment with privacy, consent, and regulatory requirements. • Partner with teams to ensure data quality, taxonomy consistency, and measurement governance. • Help clients understand tradeoffs, limitations, and risks within their data and technology ecosystems. • Own analytics workstreams end-to-end, serving as a de-facto workstream lead responsible for insight quality, delivery timelines, and managing client expectations from discovery through recommendation. • Mentor junior analysts, oversee contractor work and support capability development within the Data & Insights team. • Contribute to sales and marketing efforts through thought leadership, presentations, webinars, and proposals. • Act as a trusted analytics advisor to clients and internal teams.

• Own data collection strategies from start to finish - identifying what data we need, gathering information from various sources, and establishing data quality protocols. • Design and develop algorithms that will form the core of our platform's functionality using Python and SQL. • Interpret data, analyze results using statistical techniques, and provide actionable insights to guide business decisions. • Create and maintain databases to support our analytical needs and ensure data integrity. • Work closely with the product team to translate business requirements into technical specifications for data collection and analysis. • Help develop and optimize the algorithmic components of our matching system.

• Own and manage the full lifecycle of dashboards and reporting assets within Superset, including design, development, documentation, and user access • Partner with stakeholders in Trading, Product, and Engineering to define and deliver KPIs, metrics, and data visualizations • Build and maintain SQL-based datasets and derived tables to power reporting tools • Develop and maintain analyses around trading performance, pricing accuracy, and KPI reporting • Monitor the health and quality of data assets across pipelines and reporting layers • Support internal users in interpreting data, self-serving insights, and building lightweight reporting artifacts • Perform QA on datasets, validate dashboard accuracy, and respond to ad hoc analytical requests • Identify opportunities for standardization, automation, and improved reporting workflows • Monitor report usage and contribute to BI governance and best practices

• Leverage prior Annuity and Life Insurance experience to drive Data Governance requirements • Work with business subject matter experts to analyze, validate and utilize data for consumption by stakeholders. • Assist Data Governance team in researching and understanding customer processes, underlying integrations, and business data needs in partnership with Data Engineers, Integration Engineers, and Architects. • Collaborate with other departments, domains business and technology stakeholders, data stewards and data owners to coordinate comprehensive needs and function as a team to achieve unified objective. • Adhere to SDLC process and source code management standards, prepare project implementation plan which includes metrics, scope, acceptance, deployment process, and deliverables. • Analyze various systems data and mapping definitions, identify the patterns, translate business definitions to necessary data quality checks within the ETL process and maintain Data Governance Artifacts. • Extensively use advanced SQL skills to perform detailed data analysis, understand data patterns, behaviors and verify mapping definitions and generate data extracts based on business need. • Support Data Products by involving in discussions with the Data architects, defining the conceptual model and implementing the physical data model based on the needs of strategic project. • Leverage prior Data Governance process and tool experience and utilize Informatica Data Governance tools such as Cloud Data Profiling, Cloud Data Quality, Cloud Data Governance Catalog, Reference 360 and Marketplace for maintaining Data Governance assets and monitoring the Data Governance activities. • Coordinate with Solution Delivery and Analytics teams to create the data lineage for various systems and Tableau Dashboards using Informatica Data Catalog tool. • Collaborate with Data Architects and Data Governance Development team to design the data marts for maintaining reference data, data quality and data classification result. • Support Business and IT Solution Delivery teams with respect to Data Governance processes, Integration and Data Services standards, and Informatica Cloud tools.