• Analyze massive customer data sets, come up with actionable insights, and explain how our models perform and how we can help our customers build optimal risk management policies • Act as a Data Science advocate: deeply understand Socure’s solutions (products, models and algorithms) and customers’ risk challenges to educate and influence from a scientific perspective • Create convincing data stories to showcase how we can help our customers eliminate identity fraud, streamline their end-user experience, and support their risk management efforts holistically • Provide thought leadership and be the customer’s voice for building the next generation of Socure’s core models and product • Create tools and automated workflows to improve the speed, accuracy, and reproducibility of our analysis • Partner closely with GTM teams (Sales, Solution Consultants, Account Managers and Technical Account Managers) to derive creative ways of analysis and identify opportunities for upsell and product optimization • Build ML models when it is advantageous to explore different approaches over the established models in production

• Perform scientific clinical data review in collaboration with SRP and SRS • Establish and confirm data review expectations for assigned trials • Manage data flows and Data Management Plans

• Work with IQVIA Information Partner Services Data Science team to help address business issues and opportunities from retail pharmacies using established methodologies and machine learning and statistical analysis tools under the supervision of other Data Scientists • Collaborate with other IQVIA Information Partner Services colleagues, as needed • Use advanced Data Exploration and Machine Learning knowledge to identify and deliver business insights in partnership with Engagement Managers and other Data Scientists • Support the execution of data science projects and promote data-centric decision making • Develop machine learning and statistical models following best practices for re-usability, stability, automation and documentation including models’ assumptions • Provide expertise in statistical/ML methodologies • Support project execution following detailed guidelines under detailed to moderate supervision

• Provide leadership to the Data Science & Analytics team and foster cross-functional collaboration (including engineering, product, etc.) to align data initiatives with broader business objectives. • Report to the Chief Technology Officer and work closely with the Director of Engineering and Sr. Director of Solutions. • Design and implement machine learning models to classify contacts, predict user engagement, and identify behavioral trends. • Develop and refine metrics to quantify spiritual growth and content effectiveness. • Analyze large datasets to extract insights that inform strategic decisions, campaign performance, and digital outreach strategies. • Design and evaluate A/B tests, multivariate experiments, and causal analyses to test hypotheses and optimize messaging, user flows, and engagement pathways. • Partner with the Director of Engineering to source, clean, and prepare structured and unstructured data for analysis and model deployment. • Communicate complex data insights to stakeholders at all levels through clear narratives and effective data visualizations, enabling data-driven decision-making across the organization. • Stay informed on trends in data science, machine learning, and AI—especially those applicable to digital engagement and nonprofit work.