Top Remote Analysis Reporting Jobs in New Orleans, LA

Analyze complex content, datasets, research questions, and logical problems; verify claims through online research; summarize information; evaluate and correct AI-generated responses; and create annotations and scenarios to improve large language model performance. The role is fully remote, full-time for 16 weeks, requires U.S. English fluency, independent work, strong analytical and research skills, and an existing Gemini account with relevant conversation history.

Leads the architecture and evolution of scalable data platforms, pipelines, and data products across multiple teams. Designs Snowflake and cloud-based solutions for batch, streaming, CDC, ingestion, transformation, orchestration, and data delivery. Establishes engineering standards, governance, observability, testing, CI/CD, and reliability practices; mentors engineers; guides architecture and roadmap decisions; resolves complex incidents; and evaluates AI, automation, and MCP-enabled data capabilities.

Own analytics as an internal data product across GTM, People, Finance, and related functions. Translate ambiguous business questions into self-service data solutions, deliver executive-ready narratives, manage stakeholder priorities, and guide data-driven decisions. Serve as a marketing analytics subject matter expert across attribution, campaign measurement, lead tracking, funnel analysis, predictive modeling, and experimentation. Use SQL, modern data-stack tools, BI platforms, and AI-assisted modeling to deliver actionable insights.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Build and maintain large-scale data processing pipelines using Apache Spark (PySpark/Scala) and Python. Design ETL workflows, implement distributed data processing, use version control (Git), and work with cloud platforms (GCP/AWS/Azure).

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Leads complex private banking data management and analytics initiatives, defining data strategies, quality standards, product attributes, and integrated client views. Partners with business, engineering, analytics, AI, and Wealth teams to translate needs into dashboards, KPIs, predictive models, personalized insights, and intelligent decision-making capabilities. Serves as a subject matter expert on private banking products while mentoring junior team members and enabling platform readiness.

Supports DHA MEPRS cost-accounting activities through recurring data processing, validation, reconciliation, analysis, reporting, and customer support. Extracts and analyzes personnel, workload, financial, and other datasets using SAS, Excel, and reporting repositories. Investigates data-quality issues, troubleshoots root causes, documents findings, develops recurring and ad hoc analytical products, communicates results, and improves or automates processes.