Top Data & Analytics Jobs

As a Mid-level Applied AI Data Scientist, you will apply statistical methods and machine learning to derive business insights from data and create Tableau visualizations.

Validate, reconcile, and analyze large datasets to identify data quality issues. Investigate anomalies, perform root-cause analysis, and recommend solutions. Work with business and technology stakeholders to define and execute validation activities, produce documentation and reports, and improve data quality processes and controls.

Define, document and govern conceptual business data models and information objects across enterprise platforms. Maintain information object inventories and business glossaries, align conceptual models with enterprise architecture standards, and collaborate with Enterprise Architecture, Data Governance and business stakeholders to support adoption across transformation initiatives.

Work with business and tech SMEs to document and control data points, capture and document business processes, support solution design and change management activities, track progress and assist implementation.

Design, build, and optimize scalable data pipelines and backend services using Java and Spring Boot. Lead MongoDB schema design and performance tuning, develop secure REST APIs, deploy data workloads to cloud platforms, implement automated testing, conduct code reviews, and collaborate with onshore stakeholders and cross-functional teams to resolve technical and business issues.

Design, build and maintain end-to-end data pipelines and Dataiku DSS projects; implement data‑warehousing models; develop Python/PySpark code; ensure data quality, CI/CD, monitoring, and performance optimization; collaborate with architects, business teams and mentor junior engineers.

Join an agile team delivering data management and transformation projects for leading banks. Analyze large datasets, define requirements, perform data mapping and data quality management, modernize processes, and support implementation. Gradually take ownership of topics and lead smaller sub-projects.

Work as a business/data analyst on banking transformation projects: analyze and validate large datasets, define data quality rules, perform as-is process and data analysis, write requirements and data mappings, support implementation, and progressively lead sub-projects and small teams.

Act as a business/data analyst on banking transformation projects: analyze large datasets, manage data quality (rules/validation), perform as-is process and data analysis, write requirements, map data, support implementation, and progressively lead sub-projects and small teams.

Join an agile team delivering data management and transformation projects for major banks. Analyze large datasets, define data quality rules, map and document requirements, modernize processes, and support implementation. Gradually assume responsibility for topics, lead sub-projects, and collaborate with stakeholders to optimize data solutions.