Top Data & Analytics Jobs

Lead reporting and analytics for a business domain during a multi-year transformation. Own data migration, define business requirements, prioritize reporting roadmap, partner with tech/data teams and vendors, deploy reporting/analytics solutions (including ML-driven automation), measure KPIs, and drive adoption and value realization across cross-functional stakeholders.

Lead reporting and analytics for the finance domain, translate business requirements to product and tech teams, own data migration and roadmap, ensure data quality, enable data-driven automation and ML, coordinate organizational readiness for reporting transition, and manage stakeholder communications to deliver measurable business outcomes.

Lead reporting and analytics for a Business Transformation domain, owning data migration, roadmap, and stakeholder liaison. Define business requirements for reporting, ensure data quality, partner with tech and vendors, and drive data-driven automation and ML features to improve operations. Manage tools, KPIs, and change adoption across a multi-brand retail environment for the duration of a multi-year transformation.

The Ticketing Insights Analyst II analyzes complex ticketing data to improve operational efficiency and customer experience through automation and data storytelling while collaborating with various teams to drive insights.

The Director of Business Development will define, negotiate, and secure partnerships to expand adMarketplace's search and performance advertising across various platforms while ensuring alignment with company goals and operational integration.

The Manager of Regulatory Submissions will lead regulatory strategies and submissions for global authorities, ensuring regulatory alignment with business goals while collaborating with cross-functional teams on medical devices.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.

As a Senior Quantitative Analyst, you will develop and enhance modeling frameworks, apply quantitative methods, and collaborate to build cloud-based solutions for Capital Markets at Capital One.

The Lead Quantitative Scientist will design and lead quantitative models for lending and financial forecasting, enhancing the collectibles market's data-driven infrastructure, while collaborating cross-functionally and building a team over time.

As a Senior Quantitative Analyst, you will develop and enhance modeling frameworks, collaborate on analytical solutions, and apply quantitative methods to improve business performance in Capital Markets.

The Lead Data Engineer is responsible for designing and implementing data models, optimizing data pipelines, and ensuring data quality and reliability within a collaborative analytics team environment.

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

Conduct rigorous research using statistics and machine learning to extract patterns from datasets. Implement algorithms, back-test models, and document findings.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

Maintain and improve analytics solutions and financial/marketing models (primarily in Excel); perform ETL/data wrangling; analyze market and business data; communicate concise insights to stakeholders; drive data-informed strategic decisions and build production-ready data products or pipelines.

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.

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.

The Quantitative Analyst will develop stock selection models, enhance research infrastructure, conduct statistical analysis, and collaborate with investment teams to provide insights.

Lead revenue assurance: monitor and audit billing pipelines, build data pipelines and models (Databricks, Python, SQL), detect and prevent revenue leakage, run experiments, define metrics, and partner cross-functionally to protect and optimize subscriber revenue at scale.

Lead and modernize the People Analytics function to deliver timely, actionable workforce insights using advanced analytics, predictive modeling, AI/IA, and self-service tooling. Partner with HR, business, and tech stakeholders to prioritize use cases, ensure data quality and governance, accelerate speed-to-insight, and communicate executive-level narratives. Build and develop a hybrid analytics team, embed analytics into decision-making, and measure business impact.

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.

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 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, build, and maintain scalable ETL/ELT pipelines and batch/streaming data platforms. Develop APIs, manage databases, containerize applications (Docker/Kubernetes), implement CI/CD, and lead cross-functional teams to deliver mission-focused analytics solutions. Requires travel and TS/SCI clearance.