Вакансии: Данные

Build and deploy models that turn financial transaction data into customer insights. Work with Product and Engineering from problem evaluation through production and ongoing improvement.

Own the data function and lead its evolution toward AI-driven business intelligence. Oversee data infrastructure, analytics, experimentation, and AI-enabled workflows while partnering with teams across the business.

Build and operate data infrastructure, reporting tools, and internal applications that support business operations and decision-making. Work with business stakeholders, the executive team, and development teams to deliver solutions from concept through production.

Analyze customer behavior and company performance across web and product platforms. Define and validate event tracking, investigate conversion funnels, and provide actionable insights in collaboration with product, engineering, and BI teams.

Join an AI product analytics team to transform product usage data into insights that guide roadmap decisions. Own BI solutions, establish analytics standards, and mentor analysts on effective data communication.

Join an autonomous data-platform company as a hands-on data engineering partner for enterprise customers. Lead discovery, implementation, proofs of concept, and adoption while translating customer needs into scalable product capabilities and roadmap input.

A financial organization is seeking a mid-level Data Engineer to build reliable data solutions across complex on-premises and cloud environments. The role covers requirements analysis, development, optimization, and ownership through production.

Lead hands-on data science and AI automation for a portfolio of live mobile games. Own predictive models and agent workflows that guide player-value, retention, monetization, and growth decisions.

Lead the design, implementation, and operation of reliable production data pipelines for analytics and machine learning. This hands-on role uses Python, SQL, workflow orchestration, cloud infrastructure, Docker, and Kubernetes, with a focus on resilient and cost-efficient data processing.

Lead a multidisciplinary data team building statistical and machine learning solutions for a digital intelligence platform. Own technical direction, team development, and collaboration across data, product, and R&D functions.