Top Data & Analytics Jobs

Build and operate scalable batch and streaming data pipelines, dimensional models, ELT/ETL workflows, and trusted data products. Improve data quality, observability, reliability, performance, security, and cost efficiency across the cloud data platform. Partner with analytics, risk, finance, product, data science, and machine learning teams to support business and AI use cases. Lead technical initiatives, influence architecture, mentor engineers, and establish engineering best practices.

Leads a pricing team responsible for analyzing insurance, underwriting, claims, and business data; developing pricing models and recommendations; implementing product and rating changes; improving processes; and partnering with Underwriting, Claims, Marketing, and leadership. Manages and develops associates, prioritizes initiatives, ensures regulatory and process compliance, and communicates complex analytical findings to stakeholders.

The Data Services Intern will support data modeling, pipeline monitoring, requirements gathering, dashboard development, documentation, and data quality validation. They will work with SQL, dbt, Snowflake, BI tools, ETL technologies, and AI-assisted development tools while collaborating with engineers and stakeholders. The role offers mentorship and hands-on experience building healthcare data solutions that support clinical interventions and patient outcomes.

Own Mux’s end-to-end data platform, including ingestion, Snowflake administration, dbt transformations, orchestration, data quality, observability, and reverse ETL. Build semantic models supporting AI agents, establish governance and reliability standards, and partner with Engineering, Finance, Product, and GTM. Use AI coding tools to develop and maintain pipelines while validating output quality. The role requires strong SQL, Python, data modeling, cloud warehouse administration, and production data engineering experience.

Leads secure, scalable customer data architecture across Adobe Experience Platform and cloud environments. Designs data strategies, models, governance frameworks, ingestion and integration solutions, migrations, and real-time customer profiles. Partners with data engineers, Adobe, and clients to address data quality, security, privacy, performance, and regulatory requirements. Uses SQL, scripting, APIs, and Postman to support implementation and automation while providing technical leadership across multiple customer projects.

Analyze transactional data, money movement, Net New Assets, fee-based flows, and path-to-advice flows. Build data flows, maintain reporting, validate and reconcile data, investigate business drivers, and communicate actionable insights. Collaborate with global stakeholders, guide junior analysts, improve processes, and leverage AI tools to create efficient analytical standards.

Analyze complex banking and client datasets to identify trends, opportunities, and actionable insights. Partner with cross-functional teams, develop analytical frameworks and metrics, create executive-ready recommendations, improve analytics through automation, and ensure data quality. The role also mentors and oversees a junior team member while supporting strategic decisions for Morgan Stanley’s U.S. Banks.

Architect scalable cloud-based data and mission internet systems supporting collection, exploitation, analysis, and operational environments. Configure AWS or Azure networking, security, storage, logging, routing, backups, VPN tunnels, and multi-cloud obfuscation. Implement cloud-hosted Android emulation, conduct infrastructure fingerprinting, produce technical architecture documentation, evaluate technologies, and brief review boards. Preferred work includes troubleshooting data transfers, supporting authorization and accreditation, developing security controls, gathering requirements, and assisting with infrastructure project management.

Leads the strategy, roadmap, and delivery of enterprise business intelligence capabilities. Oversees BI products, semantic models, reporting standards, governance, adoption, and AI-assisted analytics in partnership with Data Engineering, Data Science, IT, and business leaders. Manages and develops the BI team, prioritizes demand, translates business needs into scalable products, monitors performance and value, and remains technically engaged in solution design and troubleshooting.

Leads enterprise business intelligence strategy, roadmap, product delivery, semantic modeling, governance, and AI-enabled analytics. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, IT, and business leaders to deliver trusted, scalable reporting and decision-support capabilities. Manages BI demand, adoption, performance, standards, and team development while remaining technically involved in solution design and complex initiatives.

Lead enterprise data governance strategy and operating model implementation, including ownership, stewardship, quality, metadata, classification, access policies, and regulatory alignment. Establish governance councils, define accountability, and drive adoption of cataloging, lineage, and data quality tools such as Collibra, Alation, and Microsoft Purview. Manage cross-functional workstreams, stakeholders, and delivery across regulated enterprise environments, with potential client travel of up to 80%.

Leads the technical development, deployment, and client delivery of M-NAV marketing measurement solutions. Applies marketing mix modeling, attribution, experimentation, Bayesian modeling, feature engineering, validation, and budget optimization. Partners with product, data science, marketing, media, and client teams while translating complex analytical methods into practical investment recommendations and supporting sales engagements as a subject matter expert.

Leads advanced Brand and Consumer analytics, integrating insights across marketing mix modeling, forecasting, commercial performance, and digital commerce. Develops data-driven narratives, translates complex analyses into actionable recommendations, and advises executives and stakeholders. Builds trusted client relationships across Marketing, IT, Sales, and Finance while using SQL, Python, statistical methods, and hypothesis-driven analysis to identify performance drivers and business opportunities.