Top Hybrid Data & Analytics Jobs

The Senior Analytics Engineer will manage the analytics layer, owning dbt projects, orchestrating data pipelines, defining metrics, and ensuring data quality while mentoring the data team.

Lead research strategy for Beauty, Style, and Entertainment verticals by analyzing large first-party datasets, synthesizing insights, advising marketing/editorial/sales, supporting RFPs and ad hoc requests, designing quantitative consumer research, and presenting findings to technical and non-technical stakeholders.

Lead and grow a Business Intelligence team, partner with senior leaders to prioritize analytical initiatives, ensure analytic output quality, drive BI operating model evolution, adopt modern BI tooling and self-service, and embed AI-assisted methods to improve decision-making.

Design, build, and own scalable ETL/ELT pipelines, data models, and data infrastructure. Improve data quality, observability, performance, and CI/CD for data workflows. Partner with analytics, ML, software, and product teams, mentor engineers, and resolve complex data issues.

The Staff Implementation Engineer will lead complex data integrations, develop big-data pipelines, and mentor engineers, ensuring high standards for data security and governance.

Lead analytics strategy and decision support across Product, Growth, Revenue, Operations, and Finance. Perform deep-dive analyses, design experiments, build predictive models and ML/AI prototypes, create trusted reporting and dashboards, ensure data quality, automate workflows, and partner with stakeholders to drive measurable business outcomes. Act as a primary analytics partner, prioritize work, communicate recommendations, and mentor analysts informally.

Lead analysis and insights for sports game titles; translate product and business needs into actionable, data-driven recommendations; build reports and visualizations; develop scalable self-service tools; mentor analysts and partner with Product, Marketing, and Commercial teams to drive player and business outcomes.

Lead and scale a horizontal Business Analytics team supporting multiple operational functions. Define analytics strategy, build dashboards and KPIs, translate ambiguous questions into actionable insights, coach analysts to deliver recommendations, and adopt AI tools to improve team effectiveness. Communicate findings to senior leadership and partner with cross-functional stakeholders to influence strategy and execution.

Analyze processes and operational data, gather and document business requirements, validate data, monitor KPIs, prepare reports and dashboards, recommend improvements, and support cross-functional implementation and project tracking.

Lead analytical work to monitor loan portfolio and originations, detect credit and underwriting issues, build multivariate statistical models, analyze funnels, quantify costs/benefits, present recommendations to executives, design monitoring and controls, and drive implementation using SQL, Python, Excel, AI tools, and financial/statistical techniques.