Top Data & Analytics Jobs

The Financial Crime Risk Investigator II conducts investigations of money laundering and terrorist financing, analyzes data, collaborates with law enforcement, and leads project initiatives.

Manages research data for multisite neurodegenerative disease studies by collecting, integrating, cleaning, validating, documenting, and preparing datasets for research use, reporting, transfers, and system ingestion. Develops reproducible scripts, queries, and workflows; resolves discrepancies across internal and external sources; supports cohort feasibility analyses; and coordinates with investigators, laboratories, IT teams, and research collaborators.

Conduct semiconductor market research, maintain component and application databases, develop market forecasts, validate assumptions, and communicate insights to internal teams and clients. The role owns the Application Market Forecast Tool, contributes to thought leadership, responds to stakeholder inquiries, and supports sales, renewals, and product development through actionable industry analysis.

Conducts inventories and assessments of Navy environmental data assets, converts tabular and CAD data into standardized geospatial layers, and documents methods and findings. Develops Python scripts to automate data inventory and development processes, performs validation and quality control, and manages multiple datasets and deadlines. Collaborates with teams supporting environmental, cultural resources, natural resources, and wildlife aircraft strike hazard GIS data. Power BI may be used to track project progress and data quality.

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.

Leads and mentors a SQL Developer team while designing, developing, optimizing, and securing SQL Server database solutions. Responsibilities include data modeling, T-SQL development, performance tuning, SQL Agent management, SSIS and SSRS integrations, ERP data replication, reporting structures, backups, permissions, HIPAA compliance, and data integrity. The role partners with application, infrastructure, and business teams and supports data lake initiatives such as Snowflake.

Collects, organizes, cleans, validates, and analyzes data to support business decisions. Maintains databases, monitors KPIs, identifies trends, prepares reports and dashboards, and documents findings. Collaborates with departments to understand business needs, provide data-driven insights, improve processes, and support operational efficiency.

Collects, analyzes, and manages complex datasets to produce actionable business insights. Develops data models, dashboards, reports, and automated reporting processes; validates data accuracy; identifies trends and improvement opportunities; and presents findings to management. Collaborates with cross-functional teams and stakeholders to define data requirements, evaluate performance, streamline reporting, and support data-driven initiatives.

Collects, cleans, validates, analyzes, and interprets data to support business decisions. Develops reports, dashboards, presentations, and performance measurements; identifies trends; and translates complex information into actionable recommendations. Collaborates with technical and non-technical stakeholders, communicates findings clearly, maintains data accuracy, and supports multiple analytics projects and deadlines.

Collects and analyzes business data, develops dashboards and reports, monitors KPIs, identifies trends, verifies data accuracy, and provides insights to support forecasting, planning, and informed decision-making. Collaborates with departments and technical teams to understand reporting needs, improve data processes, communicate findings clearly, and recommend business improvements.

Build and own production data infrastructure for a healthcare AI platform. Responsibilities include REST API ingestion, Azure Event Hubs streaming into Databricks, Delta Lake medallion pipelines, entity resolution, semantic metrics, data-quality instrumentation, reconciliation, schema-drift handling, and troubleshooting source-to-warehouse discrepancies. The role requires strong Python and SQL skills, independent pipeline ownership, and experience with Databricks, Spark, PySpark, streaming, and healthcare-related data is a plus.