Top Data & Analytics Jobs

Track, analyze, and report KPIs for a digital commerce workstream; identify trends and opportunities; define and track OKRs; create data-driven action plans; lead improvement projects; prioritize and define reporting; present insights to stakeholders and partner cross-functionally.

Support the Global Client Group with sales and pipeline analytics, dashboards, forecasting, and executive-ready reporting. Deliver data-driven insights, develop BI tools, and drive process improvements using AI, automation, and cross-functional collaboration to optimize sales and business performance.

Lead and scale cloud-based distributed data platforms and real-time data pipelines. Manage cross-functional on-site and offshore teams to deliver, troubleshoot, and optimize ingestion, curation, and streaming solutions. Improve AWS and data warehouse performance and cost, implement CI/CD for reliable deployments, and integrate AI-driven ops for anomaly detection and predictive data quality.

Work within Deals Tech & Data to build analytics and AI-enabled solutions for M&A and private equity clients. Analyze complex deal data, build scalable data pipelines (e.g., Databricks), develop ML models and apply Generative AI for data extraction and reporting, automate data preparation, visualize insights, mentor junior staff, and communicate solutions to stakeholders to drive transaction and portfolio value.

Build and maintain internal data application tools and frameworks for a centralized cloud data lake. Collaborate with cross-functional teams and Data Engineers to add features and maintain Go-based data pipelines. Improve platform architecture for scalability, observability, and reliability while sharing knowledge and mentoring teammates.

The GTM Engineer will innovate and enhance GTM processes at EliseAI by leveraging AI and automating workflows while collaborating across various teams.

As a Salesforce Systems Analyst, you'll enhance CRM workflows and systems, collaborating with Sales and Account Management teams to improve operational efficiency by translating business needs into scalable solutions.

Design, build, and operate big-data and streaming platforms (Kafka, Hadoop, Dremio). Develop, deploy, and monitor data pipelines using Java, Python, Spark/Flink; collaborate on data modeling and ingestion, ensure data integrity and availability, act as a Big Data SME, and perform root-cause analysis.

As a Machine Learning Engineer, you will enhance internal libraries for deep learning, collaborate with researchers, and optimize workflows for cost savings.

Lead product analytics for new financial product initiatives: build business models, segment customers, create datamarts and dashboards, ensure data quality, design experiments, and surface insights using AI-enabled tooling to guide product decisions.