Top Data & Analytics Jobs

The Data Analyst gathers, validates, and analyzes data from multiple sources to identify trends, evaluate KPIs, and generate actionable insights. They develop and maintain reports, dashboards, visualizations, and business intelligence solutions using tools such as Power BI. The role also involves partnering with stakeholders, translating business needs into analytical requirements, presenting findings to technical and non-technical audiences, documenting work, and improving reporting and analytical processes.

Leads analytics delivery across multiple clients, combining marketing data to evaluate performance, optimize investments, and inform growth decisions. Designs and implements advanced measurement approaches including attribution, incrementality testing, experimentation, and full-funnel measurement. Develops measurement frameworks, communicates insights to clients and senior stakeholders, partners with technical and marketing teams, supports new business, and mentors junior analysts.

Collect, clean, transform, analyze, and maintain fund and CRM data related to venture and growth equity. Ensure data quality, manage databases and taxonomies, conduct statistical analysis, create dashboards and reports, and track market and competitive activity. Partner with attorneys and cross-functional teams to deliver insights supporting fund practice decisions and business development.

Analyzes autonomous-vehicle data and driving scenarios to validate dataset quality, identify edge cases and coverage gaps, monitor quality metrics, and investigate anomalies. Reviews annotation batches, maintains dashboards and reports, and automates validation and testing workflows using Python, Pandas, and ClickHouse. Collaborates with product and engineering teams to improve annotation efficiency, testing processes, and data quality.

Own marketing measurement models for multiple customers, partnering with strategy managers from kickoff through model release, interpretation, enablement, and action planning. Configure and QA model inputs and outputs, manage escalations, deliver deep-dive analyses and scenario work, and support renewals and account growth. Build scalable playbooks, documentation, and AI-assisted workflows while translating complex measurement results into actionable budgeting and campaign decisions. Provide customer feedback to product, science, and engineering teams and support pre-sales and case studies.

Partners with Finance, Accounting, and internal teams to identify data sources, validate data quality, model datasets, and develop automated dashboards and reports. Translates business requirements into technical specifications, designs reporting workflows, performs DAX, Power Query, and SQL analysis, and supports process improvement and technical accounting research.

Develop and support analytical systems for operational decision-making, identify KPIs with business process owners, analyze data lifecycles, define data warehouse and ETL requirements, validate data engineering results, build dashboards, and present insights to customers. The role requires at least one year of data or BI analyst experience, strong SQL and data visualization skills, analytical communication abilities, and fluency in Russian and English.

Develops marketing data strategies, KPI frameworks, governance standards, dashboards, reports, and automated data pipelines. Audits and reconciles multi-source datasets, translates business needs into technical requirements, leads user acceptance testing, and partners with Analytics, IT, and Data Engineering teams. Provides marketing data expertise, documentation, training, and strategic insights on campaign performance, audience behavior, attribution, and personalization.

Perform independent healthcare analytics projects for clients: use statistical tools, predictive modeling, BI/reporting and data visualization. Build reports and insights using R, SAS, SPSS, Cognos, and Business Objects, and collaborate with the Senior Consultant to maintain client relationships.

Develop predictive statistical models and reports using SAS Visual Statistics and Visual Analytics to identify member behavioral trends (e.g., readmission risk). Load and analyze data in LASR, communicate methods and results to executives and analysts, and work in a distributed Linux/UNIX environment within the health insurance domain.