Top Senior Data & Analytics Jobs

Analyzes complex data to identify fraud trends and develops, tests, implements, and optimizes fraud rule strategies for new account originations. Evaluates rule performance, thresholds, segmentation, and treatment strategies; conducts champion/challenger testing; and delivers actionable recommendations. Collaborates with operations, technology, risk management, and compliance teams to improve fraud detection while balancing mitigation, customer experience, false positives, and operational efficiency.

The Business Intelligence Analyst acquires, integrates, transforms, and analyzes complex datasets to deliver insights, dashboards, reports, metrics, and recommendations. The role uses SQL, Power BI, and cloud analytics platforms to support business decisions, monitors outcomes, ensures data governance compliance, and communicates findings to technical and non-technical stakeholders. The analyst partners across business and technology teams to solve problems and improve reporting capabilities.

Leads Flexential’s enterprise data strategy, architecture, governance, integration, analytics enablement, and information management functions. Oversees data platforms, warehouses, pipelines, APIs, data products, metadata, lineage, quality, security, and governance standards. Builds an enablement-focused operating model, partners with AI and business teams, manages vendors and budgets, and develops the Enterprise Data team. The role drives trusted, reusable data assets, self-service analytics, operational efficiency, and AI readiness while improving platform reliability, delivery discipline, and measurable business outcomes.

Partners with data product owners, technical teams, and business stakeholders to identify data and analytics needs, define requirements, create user stories and acceptance criteria, and support backlog prioritization. Manages analytics support requests, investigates recurring issues and root causes, maintains legacy-report inventories, and recommends modernization and data-quality improvements. Supports adoption through documentation, training, communications, and outcome measurement while helping transition users to governed data products and self-service technologies.

Leads Zoetis’s R&D data and digital transformation, including data engineering, analytics, AI/ML, product management, governance, architecture, and digital laboratory platforms. Owns the R&D digital strategy, roadmap, and delivery of $30M+ programs across discovery through regulatory submission. Builds high-performing teams, establishes compliant data ecosystems, integrates ELN/LIMS workflows, manages vendors and operating models, and drives measurable improvements in data quality, reuse, scientific productivity, and portfolio decisions.

Leads the design, development, testing, tuning, and optimization of financial crimes detection models across AML, fraud, KYC, and sanctions. Performs statistical analysis, threshold calibration, back-testing, model efficacy assessments, feature engineering, and root cause analysis. Configures financial crimes platforms, monitors model performance, establishes testing and governance standards, and partners with Model Risk Management and leadership on validation, audit, regulatory, and risk-related initiatives.

Own executive reporting and data strategy for autonomous vehicle system performance. Lead the weekly Software Performance Review, develop board-level reporting, analyze robotics and autonomy metrics, translate technical findings into strategic recommendations, and establish data visualization standards. Partner cross-functionally across engineering and performance teams, create data-driven feedback loops, and mentor Business Analytics and Business Intelligence engineers.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Develop and maintain commercial reporting and digital enablement tools for sales, finance, marketing, and operations teams. Provide ad hoc analyses, dashboards, business reviews, trend analysis, and actionable insights to support resource deployment and decision-making. Collaborate with Salesforce product owners on functionality and feature rollouts, coordinate strategic initiatives, and translate complex data into business recommendations.

Conducts research, data analysis, interviews, and reporting to identify eCommerce site performance and customer experience improvements. Manages data and reporting requests, prioritizes work by business impact, defines KPIs with stakeholders, translates business needs into documentation and deliverables, and presents findings to management. Requires SQL, data analysis, eCommerce experience, cross-functional collaboration, and strong communication skills.

Designs and leads enterprise-scale data platforms, pipelines, lakehouses, warehouses, and streaming solutions. Establishes data modeling, governance, security, architecture, performance, scalability, reliability, and cost standards. Collaborates with engineering, analytics, machine learning, and business teams while mentoring engineers and advancing data platform best practices. Requires extensive experience with Snowflake, Databricks, BigQuery, Redshift, Spark, Kafka, cloud platforms, and modern data architectures.

Designs, builds, and operates large-scale Hadoop-based data pipelines and analytics platforms. Responsibilities include ingesting, transforming, streaming, and analyzing structured and unstructured data; developing Spark applications; managing distributed systems; supporting machine learning and reporting workloads; troubleshooting production environments; and improving platform reliability, performance, and cost efficiency.

Designs, develops, and operates large-scale Hadoop data pipelines and analytics platforms. Responsibilities include ETL/ELT, streaming pipelines, Spark and MapReduce optimization, data modeling, governance, monitoring, orchestration, cloud technology evaluation, architecture reviews, documentation, and mentoring. The role requires strong Hadoop ecosystem expertise, software engineering fundamentals, distributed-systems knowledge, SQL, scripting, and production experience with big-data platforms.