Top Hybrid Data & Analytics Jobs

Supports private-market asset data workflows by processing and reconciling data, monitoring exceptions, maintaining quality standards, analyzing trends, documenting operational logic, coordinating offshore teams, and partnering with Product, Data, and Engineering on process and product improvements.

Designs, develops, and operates scalable batch and streaming data pipelines and products. Integrates data from multiple sources, improves reliability and performance, establishes reusable engineering patterns, and supports AI, search, analytics, and machine learning workloads. Partners with technical and business stakeholders on architecture and requirements, while providing technical guidance and mentoring to less-experienced engineers.

Owns data systems workstreams for public fixed income investment operations. Leads process improvement and automation, develops reports, dashboards, and data models, manages data quality and issue resolution, and performs portfolio analysis, forecasting, benchmarking, and financial modeling. Partners with investment, client, and business teams on reporting and analytics while supporting technology implementations, translating business needs into technical requirements, and mentoring junior analysts.

Lead business intelligence initiatives supporting Snapchat’s Sales organization. Analyze data from multiple sources, identify campaign and industry trends, build dashboards and reports, deliver actionable revenue insights, and recommend optimization strategies. Partner with cross-functional teams on measurement strategies, product feedback, revenue programs, and growth initiatives. Communicate complex analyses to technical and non-technical audiences and influence business decisions through compelling data stories.

Own wholesale performance reporting and analysis across retail partners, products, and regions. Build datasets, data models, dashboards, and automated reporting while validating data quality. Analyze sell-through, inventory, pricing, promotions, and commercial trends to identify growth opportunities. Partner with stakeholders across Wholesale, Digital Commerce, and Marketing to frame analytical questions, communicate findings, and provide actionable recommendations.

Develop and monitor fraud-detection models and pattern-recognition algorithms for lending products. Analyze large datasets using Python and SQL, identify emerging fraud trends, and collaborate with Fraud Operations to refine features and reduce false positives and negatives. Conduct ad hoc analyses, recommend risk and verification strategies, communicate findings to cross-functional partners, and support improvements to underwriting and verification processes.

Build, optimize, and maintain scalable data pipelines and reusable datasets for business intelligence, marketing, and data science. Develop a federated data validation framework, optimize queries and data models, and protect sensitive healthcare data through privacy and security best practices. The role uses Python, SQL, AWS, Airflow, PostgreSQL, Snowflake, and modern data-stack technologies. This position is based in New York City and requires working onsite three days per week.

The AI Analyst Co-op will use Python, HTML, SQL, APIs, and AI tools to generate scalable insights for go-to-market teams. Responsibilities include personalizing BDR outreach by buyer persona, distributing market insights across sales, marketing, and partner resources, and collaborating with Platform Advisory. The role requires strong analytical skills, attention to detail, problem-solving persistence, and an understanding of technology’s role in improving operational efficiency.

Leads a team of 7–8 analytics professionals supporting user growth, activation, engagement, retention, conversion, and rentals analytics. Owns experimentation strategy, A/B and multivariate testing, KPI frameworks, funnel diagnostics, dashboards, Snowflake data models, and Tableau self-service analytics. Partners with Product, Engineering, Design, and Finance to guide growth investments and senior-level decisions. The role also requires hiring, coaching, AI-enabled analytics workflows, and strong statistical and causal reasoning.

Collects, processes, vets, and analyzes geospatial and statistical data using Esri tools, Power BI, Python, or R. Supports research projects, client meetings, reports, presentations, dashboards, technical assistance, and proposal development. Works on focused project tasks under supervision while communicating findings clearly and maintaining project information and spending records. The role is hybrid in Houston and includes travel to client sites.