Top Data & Analytics Jobs

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 Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.

Develop and optimize high-volume Teradata data warehouse applications: design/architect solutions, model data, write and tune SQL, use Python scripting; ML and Hadoop experience a plus.

Design and architect data solutions and large-scale Java/J2EE systems. Define extensibility, scalability, availability and security requirements. Document current and target state, gather functional and non-functional requirements, recommend process optimizations, and consider impacts of existing infrastructure and networks.

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.

Lead design, build, and deployment of secure, scalable data pipelines and analytics platforms (including Palantir) in constrained or classified environments. Mentor multidisciplinary teams, integrate AI/ML and LLM capabilities into production workflows, implement DevSecOps practices, and communicate architectures to technical and nontechnical stakeholders.

Advise executive leadership on data strategy and deliver automated reporting and analytics. Design and maintain enterprise BI models, semantic layers, and KPIs. Enforce Power BI standards, optimize data warehouse and ETL workflows, integrate diverse data sources, ensure data quality and governance, use embedded AI/ML for predictive insights, and present findings to executives. Lead training to raise data literacy and support strategic projects.

Lead configuration and integration of financial and operational systems for multi-property hospitality lines. Manage ERP/PMS implementations, data governance, payment/merchant setups, reporting mappings, vendor relationships, process automation, and stakeholder change management to improve financial reporting and decision-making.

Support AFSOC data integration and modernization by building and optimizing ETL pipelines, integrating diverse data sources, managing NoSQL and big-data infrastructures, configuring analytics frameworks, administering cloud and CI/CD tooling, and coordinating with stakeholders to enable downstream analytics and machine learning.

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.

As a Senior Data Analyst for Fraud Strategy & Operations, you will analyze data to identify fraud trends, build predictive models, design fraud prevention rules, and collaborate with cross-functional teams to enhance fraud detection capabilities.

As the Senior Fraud Strategy and Analytics Manager, you will analyze fraud trends, build predictive fraud models, implement prevention rules, and enhance risk profiles while collaborating with cross-functional teams in the financial services sector.

The role leads the transformation of reporting and analytics for consumer product quality, focusing on complaint data analysis and driving quality improvements globally.

The Data Scientist role involves analyzing payment and subscription experiences, applying data science methods, and collaborating with cross-functional teams to improve player experiences and business decisions.

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.

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

Lead and manage global teams delivering commercial analytics and technology initiatives for Life Sciences, while driving projects related to field force design and sales effectiveness.

Design and execute advanced inferential and predictive analyses and study designs for population and behavioral research. Support survey weighting, variance adjustments, sample blending, data preparation and quality monitoring. Contribute to technical deliverables, literature reviews, causal inference and synthetic data solutioning, visualizations, and stakeholder communication while collaborating with interdisciplinary teams and HPC engineers.

The Quantitative Research Analyst will develop execution strategies, conduct market research, and analyze execution costs for Futures and FX trading.

The Senior Data Scientist will develop optimization models, manage the model lifecycle, and collaborate across teams to enhance Lyft's marketplace efficiency and strategy.

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

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.