• Design and iterate data extraction and transformation pipelines that convert unstructured leasing documents into structured JSON stores. • Write and optimize LLM API calls and prompts to extract and interpret text data at scale. • Orchestrate AI-driven workflows integrating multiple LLM models to handle diverse document types and edge cases. • Build and maintain ELT workflows in Python, managing data flows between cloud storage and relational databases. • Develop data quality and validation frameworks to ensure structured outputs are accurate and production-ready. • Implement monitoring, alerting, and automated quality checks across extraction pipelines. • Collaborate with product and engineering teams to define and evolve data schemas. • Own the pipeline end-to-end — from raw ingestion to validated structured output.

• Build and lead Battle Road’s data platform from the ground up. • Architect our AWS-based data warehouse and ingestion pipelines • Transform high-volume simulation outputs into clean, trusted datasets • Establish schema standards and data contracts with engineering • Enable scenario replay, comparison, and traceability • Support analytics and AI workflows across the platform • Hire and develop a high-performing data engineering team • Within your first year, you will stand up a scalable warehouse, integrate core simulation feeds, and deliver reliable insight into product usage and simulation behavior. • You will be modeling a dynamic world state, not just logs.

THE TEAM & THE JOB We are seeking a talented and self-motivated Senior Data Scientist/AI Engineer to join our team. In this role, you will design, build, and deploy next generation AI-driven tools for market research. You will work at the intersection of data science and AI engineering. We develop models and predictions using a combination of surveys, voter databases, census microdata, behavioral tracking and other sources. We handle the most difficult data problems at our company, including massive datasets, missing data, self-selection, measurement error, fraud detection, attrition, and many more. This is a hands-on role that requires both analytical and programming skills at an advanced level. WHAT YOU WILL BE DOING Design and build AI-powered applications to analyze, summarize, and generate insights from survey data. Contribute to technical design and architecture decisions for AI/ML systems. Develop and optimize prompts and chains. Build applications to simplify analytics and improve the efficiency of data processing. Work with structured and unstructured data Collaborate with data analysts, product managers, UI designers, and software developers to create great products. Contribute to model evaluation and performance tracking using both qualitative and quantitative metrics. Stay up to date with recent developments in AI and machine learning, including LLMs, fine tuning, and RAG pipelines. Handling ambiguous, complex problems with minimal guidance Contribute to technical vision, architectural decisions, or to help setting technical standards. Contribute to business impact and strategic problem-solving at an organizational level as and when required. KEY COMPETENCIES Master’s or PhD in data science or related field. Demonstrable progressive experience in senior data science/AI engineering roles. Advanced knowledge in Python and/or R for data analysis, modelling, and visualization. Experience working with LLM APIs and building LLM-based applications and frameworks. Progressive experience with natural language processing, including topic modelling, text classification, and summarization. Experience in taking part in cross-functional technical projects. Ability to write clean, maintainable, well-documented code. Proven track record of delivering complex, high-impact solutions. Ability to cross collaborate with other teams across the business. For roles based in California, New York, Colorado or Washington State, the base salary hiring range for this position is USD 188,864 - USD 211,600. Compensation offered will be determined by multiple factors including location, job-related knowledge, skills and experience. Certain roles may be eligible for incentive compensation and additional benefits. All US based full time employees are eligible for the following benefits: Paid vacation, holidays and sick days Flexible working arrangement available Group medical, dental and vision insurance Company-paid life and disability insurance Paid parental leave 401(k) with company match Why join YouGov? Join our global team to help us achieve our social mission: to make millions of people’s opinions heard for the benefit of our local, national, and international communities. Understanding diversity of opinion requires diversity of background. Although our global panel of millions of people worldwide powers our research, our biggest asset is our people. If our research is to be truly representative of what the world thinks, we need people from all walks of life to be part of the team to bring their perspective to the work we do. Life at YouGov We are driven by a set of shared values. We are fast, fearless, and innovative. We work diligently to get it right. We are guided by accuracy, ethics, and proven methodologies. We respect and trust each other, bringing these values into everything that we do. We strive to provide YouGovers with best-in-class benefits to support their physical, financial, and emotional wellbeing. We want our employees to have a sense of belonging and uniqueness in a supportive workplace, so they can bring their full selves to work. Equal Opportunity Employer As an Equal Opportunity Employer, qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity or expression, and sexual orientation), parental status, national origin, marital status, age, disability, genetic information, HIV status, political affiliation, socioeconomic background, veteran status or any other characteristic protected by law or in line with our responsibilities as a fair and ethic employer. All employment decisions are made based on occupational qualifications, merit, and business need.

• Lead the foundational setup of new data environments, including Snowflake provisioning, SSO configuration, and initial system architecture. • Design, build, and manage scalable data pipelines and ETL/ELT processes to transform raw data into actionable insights. • Support the scaling of engineering teams to handle high volumes of commercial projects while maintaining business continuity during organizational transitions. • Develop and maintain robust DBT data models to support semantic layer build-outs and advanced analytics capabilities. • Partner closely with business leaders and stakeholders to bridge the gap between technical delivery and strategic objectives. • Provide engineering support for custom backend applications, ensuring seamless data integration and reliable exposure to end users. • Establish and enforce best practices for data engineering, architecture, and deployments that can scale across multiple organizations.