Chief Data Officer (CDO)

ABOUT YOU The CDO will be a key member of the executive leadership team, responsible for defining and implementing Xsolla's enterprise-wide data strategy. Data plays a critical role in improving monetization outcomes for game developers, and this leader will own that strategy end-to-end — from vision and governance through hands-on execution — ensuring that the insights we generate translate directly into better monetization performance for our customers. This is a hands-on, technically fluent leadership role. The ideal candidate brings a strong background in machine learning and AI, with the ability to personally guide the development of models, design rigorous A/B testing frameworks, and evaluate model performance to identify and scale the improvements that move the needle for game developers.

ABOUT US

Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com.

Responsibilities:: Define, own, and evolve Xsolla's company-wide data strategy, aligning data initiatives with the goal of improving monetization outcomes for game developers and publishers. Translate strategy into execution: build and lead the teams, roadmaps, and infrastructure needed to turn Xsolla's data into a durable competitive advantage. Partner with product, engineering, marketing, and operations teams to identify where data and machine learning can directly increase developer revenue and player lifetime value. Build, guide, and evaluate machine learning and AI models — designing controlled A/B and multivariate tests to compare model approaches and rigorously validate which produce measurable monetization improvements. Establish a scalable experimentation culture, including test design standards, statistical rigor, and clear frameworks for deciding when a model or approach should be rolled out broadly. Own data governance, quality, security, and privacy practices, ensuring compliance with relevant regulations (e.g., GDPR) and internal policy across all markets Xsolla serves. Build and scale a high-performing data organization, including data science, analytics engineering, and ML engineering talent. Hire and grow a strong team of data scientists and analysts, setting the technical bar and career development path for the function. Break down data silos across the organization and champion a data-driven culture among executive peers and cross-functional teams. Report on data strategy progress, model performance, and monetization impact to the CTO and executive leadership team.

Qualifications & Skills:: Proven experience as a CDO, VP of Data/Analytics, or in a comparable senior data leadership role, ideally within gaming, monetization, payments, or a related technology sector. Strong hands-on background in machine learning and AI, with direct experience building, training, and evaluating models — not solely managing teams that do. Demonstrated experience designing and running A/B tests or other experimentation frameworks to compare model or product variants and drive decisions from the results. A track record of translating data strategy into measurable business outcomes, ideally tied to revenue or monetization growth. Deep knowledge of data governance, data architecture, and modern data infrastructure (cloud data platforms, pipelines, MLOps). Strong executive presence and communication skills, with the ability to influence peers, the board, and cross-functional stakeholders. Bachelor's degree in a quantitative field (Computer Science, Statistics, Data Science, Engineering, or related); advanced degree preferred. 10+ years of progressive experience in data, analytics, or ML leadership roles, including experience building and scaling teams. Experience working within a high-performing organization that measures success by results and impact rather than activity — and holds their team to that same standard.