Top Analytics Jobs in Buffalo, NY

Lead design and expansion of a unified analytics data platform integrating Medicare claims, clinical systems, and vendor feeds. Implement AI-augmented data engineering (LLM coding assistants, automated QA, autonomous data-quality agents), build validation/reconciliation/audit infrastructure, partner with analytics teams for reporting and modeling needs, and drive large-scale analytics platform and web app implementation while collaborating with IT on security and deployment standards.

Lead the design and implementation of analytics solutions, manage Adobe Analytics migrations, ensure data governance, and deliver cross-channel insights for customer journey optimization.

The CJA Business Analyst translates business analytics requirements into actionable tasks within Adobe Customer Journey Analytics, ensuring accurate reporting and effective migration from Adobe Analytics. Responsibilities include requirement gathering, validation, documentation, and collaboration with stakeholders.

The role focuses on providing analytics services to game studios, including A/B testing, revenue analysis, and data contextualization for decision-making.

The Director, Ecommerce and Marketing Analytics leads analytics across multiple business functions, transforms data into insights, governs AI workflows, and establishes analytical standards to drive decisions and actions throughout the organization.

Manage performance, reliability, and accountability for high-volume messaging programs. Build dashboards and alerting, run ad hoc analyses, coordinate incident response and vendor testing, conduct post-incident reviews, and maintain documentation and compliance tracking to inform program decisions and improvements.

Lead capacity planning and commercial analytics: build and maintain capacity reporting, dashboards, and NetSuite inventory processes; enforce data governance and KPIs; partner with Sales, Finance, and Operations to enable data-driven commercial decisions and scalable growth.

The Staff Product Analytics Engineer will enhance product data usage across teams by owning data infrastructure, creating tools for self-service data, and ensuring data-driven decisions. Responsibilities include collaborating with various teams to improve data insights and maintain data pipelines.

Lead Analytics Engineer responsible for end-to-end data solution design, evolving data architecture, mentoring engineers, driving data health and observability, enabling cross-functional measurement, and contributing to roadmap and decision-making.

Lead and build Harvey’s people analytics function: design the people data architecture, consolidate HR systems, define metrics and methodology, create dashboards and forecasting models, surface leading indicators for intervention, enable self-serve analytics, and partner with People Ops, Recruiting, Finance, and Data Engineering to drive strategic workforce decisions.

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

Lead revenue operations and business insights by owning GTM and revenue data integrity. Build reporting and AI-driven insights, run billable usage analysis, manage data flows with Fivetran/Salesforce/Sigma, investigate billing disputes, and translate data into actionable narratives for leadership.

Build end-to-end data and analytics features: ingest and model data, build transformations and pipelines, create client-facing dashboards and interfaces, and develop LLM-powered workflows to accelerate analysis and app development. Partner with stakeholders, perform exploratory analyses, and ensure data quality, observability, and maintainability while influencing data engineering strategy.

Design, support, and improve data analytics solutions (OAC and Power BI). Manage data ingestion, ETL, data quality, access, and documentation. Liaise with stakeholders, migrate dashboards from OAC to Power BI, and follow SDLC and project management practices.

Manage underwriting analytics, collaborate with cross-functional teams, drive operational improvements, and enhance training for underwriters.

As a Senior Data Scientist in Marketing Analytics, you'll partner with Marketing to solve problems, design data-driven solutions, lead experimentation, communicate insights, and operationalize solutions for business impact.

Manage end-to-end analytics projects, lead cross-functional teams, ensure client satisfaction, and utilize AI tools to enhance data insights.

Manage model risk governance activities, produce complex reports, oversee risk metrics, assess model candidates, support audits, and lead projects.

Analyze commercial data for sales, marketing, service and support to create metrics and insights for optimization. Collaborate with cross-functional teams to provide data-driven recommendations and manage business intelligence tools.

Lead and manage data science teams to build models and drive business solutions; oversee compliance analytics and ensure data quality.

The Predictive Analytics Consultant designs and delivers analytics solutions for lending operations, focusing on predictive modeling, data transformation, and stakeholder communication.

Analyze ACH transaction data to enhance payment decisioning performance. Identify trends, evaluate data impact, and optimize risk strategies using Python and SQL in a fintech environment.

The Senior Data Analytics Manager leads analytical initiatives for Student Success Center operations, translating operational needs into data-driven insights to enhance agent performance and student outcomes through frameworks and dashboards.

Lead a team of analysts in Fraud & Safety operations, defining KPIs, designing experiments, optimizing performance, and enabling data-driven decisions globally.

Own and build reliable analytics data products: define metrics, create and maintain dbt models, design dashboards for growth/finance/ops, improve data quality via testing and monitoring, and enable self-serve analytics for stakeholders.