Top Data & Analytics Jobs

Design and deliver full lifecycle enterprise and big-data architectures, translate complex functional and technical requirements into detailed designs, lead presales and client presentations, perform advanced analytics and ML modeling (logistic/linear regression, random forest, neural networks, time series), define data requirements and analytical plans, and collaborate with cross-functional teams and stakeholders.

Design and implement Tableau BI solutions; work with Big Data stack (Hive, Pig, MapR, Spark); develop ETL (Datastage, Unix scripting); apply Scala/Python for machine learning; leverage AMEX domain expertise.

Analyze A/B experiments and large datasets to determine why experiments performed well or poorly. Communicate results to business partners, validate and improve data-driven decision processes, build key metrics and modeling reports, and collaborate with business and engineering stakeholders.

The Research Engineer will design and build evaluation systems to measure data quality for Firecrawl's web data extraction, creating metrics and benchmarks, and collaborating on model improvements.

The Senior Product Manager will lead strategy and execution for data products within the Global Data & Analytics team, focusing on analytics, ML, and AI use cases while partnering with engineering and stakeholders to deliver scalable solutions.

Lead enterprise data governance strategy, policies, and operating model. Define data standards, quality metrics, and lifecycle management. Partner with data stewards, IT, legal, and executives to enforce privacy, compliance, and responsible AI practices. Provide technical leadership for data architecture, integration impact assessment, infrastructure tuning, and escalation support while driving stakeholder alignment and measurement for IT steering.

The Head of Data will define and execute Crosby's data strategy, build data systems, enhance AI performance, drive analytics, and lead the data team.

DiffUSE seeks individuals interested in interdisciplinary roles involving computational biology, machine learning, and open scientific tooling. Responsibilities include data processing, ML research, infrastructure engineering, and community building.

As an Engineering Manager, you'll lead efforts to enhance model performance, manage team projects, and support professional growth in a dynamic environment.

Agap Technologies, Inc. offers online Machine Learning training with real-time instruction, immediate support, interview training, and OPT guidance for enrolled trainees.

Design and implement scalable Snowflake-based data architectures on cloud (Azure/AWS). Build and optimize ETL using SnowSQL and Spark, tune performance, migrate data systems, document designs, collaborate with stakeholders, and mentor engineers while incorporating agentic AI into the data engineering SDLC.

Lead implementation of metadata governance and lineage for structured and unstructured data in cloud environments. Ensure metadata synchronization across catalogs, ESRI/Kubernetes, and enterprise repositories. Apply OpenLineage/Apache Atlas or similar tools, enforce DoD/NSG geospatial metadata policies, and advise clients on metadata strategy and integration.

Design, build, and deliver Power BI dashboards and analytics solutions using AWS, SQL, and Python. Develop data models, ETL pipelines, and analytics logic; incorporate AI/ML where appropriate. Partner with stakeholders, IT, and vendors to gather requirements, test solutions, and translate insights into business decisions to improve customer experience for a utility program.

Lead global pricing strategy and modernization for wholesale and specialty insurance, driving analytics, AI/ML integration, pricing model governance, catastrophe and transaction-level pricing support, and talent development to improve underwriting performance and return on capital.

Conduct execution-quality research across global markets: model market impact and slippage, design A/B tests and causal analyses, build optimization and simulation tools, and deliver analytics and decision support to traders and PMs for improved order routing and execution.

Implement, install and administer an advanced analytics platform and workspaces (SAS, Tableau, R, ML). Ensure IT policy compliance and service levels, support connectivity to data sources (Hadoop, Oracle, SQL Server), perform capacity planning, performance tuning, document procedures, troubleshoot issues, coordinate implementation with architects and service providers, and automate platform administration with scripting.

The role involves leading data science initiatives, managing large datasets, developing predictive models, and building a high-performing analytics team.

Lead development of advanced analytical and machine learning models to optimize forecasting, inventory placement, and supply chain flows. Automate reports, analyze large datasets, deliver insights to leaders, drive cross-functional initiatives, mentor junior analysts, and recommend process improvements to boost operational performance.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

The Manager, Data Governance will lead the implementation of data governance strategies to support AI and analytics, ensuring data quality, compliance, and ownership while promoting data literacy across the organization.

Design, build and maintain a self-service data platform to enable teams to create data products. Support real-time analytics, batch processing and ML workloads. Implement secure, scalable, compliant infrastructure with IaC and automation. Enable ingestion, processing and consumption of data at scale. Mentor teammates and drive engineering excellence.

The Clinical Statistician will provide statistical expertise and analysis in clinical research, focusing on high-dimensional data and methodologies, collaborating with medical groups for reports and FDA submissions.

Build and maintain reports and dashboards, analyze large operational datasets (flight activity, utilization, ground/FBO), apply statistical and ML methods including LLM-assisted analysis, automate workflows, lead analytics projects, and translate recurring operational questions into repeatable tools to drive decisions.

Lead digital marketing measurement and data science, analyze digital data, develop statistical models, and collaborate with marketing teams for optimization and insights.

The Data Analyst will conduct full lifecycle analysis, develop reporting capabilities, monitor performance, and identify improvements in data quality and efficiency.