• Analyze, evaluate, and improve the quality of multilingual text classifier outputs. • Partner with linguistics and engineering teams to develop and refine language-specific parsers. • Translate and validate taxonomy content such as Skills, Titles, and Occupations from English to Dutch (and/or Dutch to English as needed). • Identify patterns in data errors and contribute to ongoing improvements in rules, logic, and workflows. • Document findings clearly and follow established processes to ensure consistency and quality.

• 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