Company Overview ID.me is the next-generation digital identity wallet that simplifies how individuals securely prove their identity online. Consumers can verify their identity with ID.me once and seamlessly login across websites without having to create a new login and verify their identity again. Over 140 million users experience streamlined login and identity verification with ID.me at 20 federal agencies, 44 state government agencies, and 66 healthcare organizations. More than 600 consumer brands use ID.me to verify communities and user segments to honor service and build more authentic relationships. ID.me’s technology meets the federal standards for consumer authentication set by the Commerce Department and is approved as a NIST 800-63-3 IAL2 / AAL2 credential service provider by the Kantara Initiative. ID.me is committed to “No Identity Left Behind” to enable all people to have a secure digital identity. To learn more, visit https://network.id.me/ . ID.me is looking for a Data Scientist to help pioneer the Data Science function with the company, and to drive Data Science for Marketing and Lifecycle Communications. By filling this role, ID.me will be equipped to manage the growing complexity of data interactions and member expectations effectively. The Data Scientist V will play a critical role in enhancing the security, usability, and personalization of the ID.me platform, driving increased satisfaction and engagement among members and partners. This position will be pivotal in transforming ID.me into a trusted, centralized service for identity and data management across the digital landscape. Responsibilities Data Analysis and Integration: Analyze large datasets to understand patterns and trends in member behavior and data accuracy. Develop algorithms and models to integrate member data seamlessly across various platforms, ensuring data integrity and relevance in real-time during member authentication processes. Machine Learning and Predictive Modeling: Design and deploy machine learning models to predict member data changes, such as address or contact information updates. Use predictive analytics to anticipate member needs and reduce friction in updating and authorizing data across multiple platforms. Data Quality Assurance: Implement robust data validation and cleansing techniques to ensure the accuracy and quality of data used across the network. Continuously monitor data quality metrics and develop automated systems to correct inconsistencies and errors in real-time. Profile Management Innovation: Lead initiatives to create dynamic member profiles that align with various use cases and contexts, enhancing personalization and relevance of data. Work closely with the UX team to integrate these profiles into partner authentication screens and ID.me's own interfaces effectively. Cross-functional Collaboration: Collaborate with technical teams, product managers, and business stakeholders to enhance the ID.me platform's functionality, focusing on data governance and the secure sharing of sensitive information. Ensure that all data handling complies with relevant regulations and ethical standards. Data Governance and Strategy: Develop and oversee data governance policies that support scalable, secure, and efficient data operations. Advise on the strategic use of data and analytics to drive business decisions and improve the member experience. Data Governance and Strategy Translate insights into narratives that enable marketing investment decisions at the executive level. Marketing and Lifecycle-Specific Responsibilities Campaign and Channel Analytics: Analyze performance across paid, owned, and earned channels, providing funnel analysis (impressions → leads → conversions), channel ROI metrics (CPC, CPL, LTV), and real-time dashboards to guide tactical optimization. Audience Insights and Segmentation: Use behavioral and demographic data to construct audience segments, journey maps, and high-value member personas to inform campaign targeting and personalized communications. Forecasting and Target-Setting: Utilize historical performance, market benchmarks, and predictive modeling to forecast campaign and channel outcomes and inform goal-setting processes. Experimentation and Optimization: Design and evaluate A/B tests and multivariate experiments to refine messaging, creative, and media mix; guide the Marketing team in data-driven optimization loops. Churn and Retention Analytics: Build models that identify at-risk members and recommend interventions to increase lifecycle retention and re-engagement. Marketing Mix Modeling: Support budgeting and planning by quantifying the relative impact of various channels and tactics on business outcomes. Basic Qualifications 7+ years of hands-on experience in data science for a SaaS company or a mature startup BS/MS in Data Science or a related quantitative or scientific field 3+ years of experience working with SQL and Python. The annual base salary listed does not include a company bonus, incentive for sales roles, equity and benefits which will be determined based on experience, skills, education, relevant training, geographic location and role. ID.me offers comprehensive medical, dental, vision, health savings account, flexible spending accounts (medical, limited purpose, dependent care, commuter benefit accounts), basic and voluntary life and AD
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