• Develop and implement AI agents (assistants, copilots, and intelligent automations) for different areas of the company. • Structure interaction flows and the decision logic of agents, ensuring the quality and consistency of responses. • Integrate AI models with corporate data, APIs, and internal systems. • Conduct testing, tuning, and continuous improvements — prompt engineering, model tuning, and performance evaluation. • Support the evolution of solutions based on LLMs and NLP, ensuring alignment with business use cases. • Collaborate with Tech Leads, Delivery, CX & AI, and AI Enablement to ensure alignment between technology, experience, and delivered value. • Monitor agents’ performance and usage, proposing continuous improvements. • Follow governance, security, and responsible AI usage guidelines.

• Design, validate, and deploy robust, scalable optimization frameworks and distribution models to ensure complete mathematical integrity across downstream metrics. • Explore and execute complex methodologies, evaluate methodological trade-offs, and implement advanced statistical procedures. • Partner cross-functionally to transition ad hoc code into standardized, version-controlled templates and logical libraries to ensure analytics are structured cleanly to power diverse product surfaces. • Partner closely with Data Engineering to optimize code performance and scale analytical workflows, helping transition complex statistical calculations from standard database queries into efficient, production-grade cloud compute architectures.

Role Description We are looking for a Data Scientist to join our core Panel Science team. Our team is dedicated to building an uncompromising, mathematically rigorous single source of truth for enterprise consumer analytics. In this role, you will work across a highly sophisticated data engine that bridges foundational statistical modeling, complex data infrastructure, and advanced analytical product architecture. Whether your deep expertise lies in refining core statistical baselines, optimizing heavy computational models, or architecting scalable logic libraries, you will have a massive impact on how enterprise-level consumer insights are delivered. This is a remote-friendly opportunity that can sit in NYC (where our headquarters is located), one of our office hubs, or anywhere else in the US. However, depending upon where the remote work is performed, income could be subject to New York State tax withholding. We expect East Coast work hours. As Our Corporate Data Scientist, You Will: - Statistical Modeling & Distribution Optimization: Design, validate, and deploy robust, scalable optimization frameworks and distribution models to ensure complete mathematical integrity across downstream metrics. - Methodology & Panel Foundations: Explore and execute complex methodologies, evaluate methodological trade-offs, and implement advanced statistical procedures. - Analytical Logic & Governance: Partner cross-functionally to transition ad hoc code into standardized, version-controlled templates and logical libraries. You will ensure analytics are structured cleanly to power diverse product surfaces, ranging from interactive dashboards to LLM-driven applications. - Infrastructure & Performance Optimization: Partner closely with Data Engineering to optimize code performance and scale analytical workflows. You will help transition complex statistical calculations from standard database queries into efficient, production-grade cloud compute architectures. Qualifications - 4–5 years of professional data science experience. - 2-3 years of experience with an advanced degree. - Bachelor’s degree in a highly quantitative field (Statistics, Economics, Physics, Mathematics, Engineering, or a related discipline). A Master’s degree is strongly preferred. - Exceptional expertise in working with, modeling, and optimizing for statistical distributions. - Advanced proficiency in Python or R and expert-level SQL. Requirements - Direct experience working with panel data or longitudinal consumer data. - Hands-on experience analyzing receipt data or transaction-level consumer data. - Experience working with Databricks and scaling advanced compute workloads. Benefits - Flexible work hours and flexible vacation. - Generous 401K match. - Parental leave. - Team events. - Wellness budget. - Learning reimbursement. - Annual on-target earnings for this position are anticipated to be up to $170K + bonus element. - Equity included in the compensation package.

• Leads the analysis of large-scale, real-world data sets, supporting stakeholders in business, clinical sciences, research sciences, regulatory, and other diverse functions. • Translates general queries into testable hypotheses and data driven answers. • Clean up, interpretation, and translation of messy data to diverse audiences. • Leads the statistical analysis design process supporting IVD-level product and QC method development studies while adhering to appropriate regulatory guidance, including CLSI and Design Control. • Independently writes and contributes to study protocols, data analysis, and final reports in working with other scientists in the group. • Facilitates consensus approval for development study protocols, coordinating input from various technical stakeholders to ensure statistical plans meet business needs and CLIA/CAP, ISO and FDA requirements. • Utilizes internal processes and tools that support efficient document writing and life-cycle maintenance. • Contributes to analysis of NGS immunosequencing data, which will require developing innovative methods for statistical analyses for big complex data generated through the experiments. • Present results to diverse audiences, including a variety of cross-functional senior leadership, clinicians, and executives. • Be a problem solver: communicate well, ask questions, proactively eliminate bottlenecks, and be the person people go to when they want a job done right • All other duties as assigned.