Top Remote Data & Analytics Jobs

Research and verify mental health service directory records, including addresses, hours, contacts, costs, insurance, and eligibility tags. Apply screening criteria, cite supporting evidence, identify new local services, and flag records that do not fit the data model. The role requires careful spreadsheet organization, adherence to written procedures, accurate source checking, and clear communication with service organizations.

Analyze behavioral, transactional, and interaction data to identify fraud patterns and emerging threats. Develop monitoring frameworks, dashboards, and mitigation solutions; evaluate AI fraud-review decisions; and translate findings into prompt, rule, workflow, and machine-learning feature improvements. Collaborate with Fraud Operations and Machine Learning teams, participate in code reviews, and mentor junior analysts. The role requires strong SQL and Python skills, statistical analysis expertise, business judgment, and fraud analytics experience.

Design, develop, and maintain data pipelines, ETL processes, integrations, data infrastructure, and complex data models. Build and support data warehouses and analytics solutions using SQL, PL/SQL, Oracle, Snowflake, and cloud technologies. Collaborate with analysts, architects, developers, data scientists, and business stakeholders throughout the delivery lifecycle. Provide production support, troubleshoot issues, tune database performance, and contribute to data-driven reporting and AI tools.

Leads the design and implementation of business intelligence solutions, maintaining Power BI data models and building enterprise dashboards for finance, human resources, and conservation programs. Investigates business questions, translates requirements into technical specifications, guides analytics projects, enables self-service analytics, and advances AI-enhanced workflows. The role also supports data governance, documentation, troubleshooting, stakeholder communication, and data-driven decision-making.

Lead analytics support for Fetch’s Food and Beverage vertical, serving as the primary analytics partner for Sales and client stakeholders. Own sub-vertical partnerships, manage analytic capacity, answer senior-level client questions, and guide campaign strategy. Use SQL to manipulate data, develop actionable insights, support QBR storytelling, and communicate recommendations to technical and non-technical audiences. Represent analytics cross-functionally and automate insights using AI-enabled tools.

Supports dataset collection, cleaning, analysis, visualization, reporting, A/B testing, and performance tracking for education products. The intern will identify trends in student, educator, and product usage data, build dashboards, document analytical frameworks, and communicate insights to technical and non-technical teams. This is a paid, remote 10-week internship with a two-day in-person experience at Amplify headquarters in Brooklyn.

Analyze Amazon Marketing Cloud, advertising, retail, and commerce data to develop custom queries, reporting, dashboards, tests, forecasts, and actionable client recommendations. Partner with commerce and client teams, explain technical findings, validate data quality, document methodologies, and improve analytics workflows. Support platforms including Amazon, Walmart Connect, and Scintilla while using SQL, BI tools, and optionally Python or R for custom analysis and lightweight modeling.

Performs structured data analysis under senior guidance to solve customer problems, identify patterns and anomalies, test hypotheses, and develop reusable data science components. Collaborates with engineering, mission operations, solution delivery, and customers to scope requirements, improve processes, and translate analytical findings into actionable business decisions. The role requires strong communication, coachability, analytical coding ability, and willingness to travel up to 50%.

Build and operate cloud data capabilities, including ingestion pipelines, transformations, data models, curated data products, and data-quality controls. Use Snowflake, dbt, SQL, and Python to deliver governed data for analytics, applications, automation, and AI workflows. Implement testing, CI/CD, documentation, lineage, access controls, monitoring, incident resolution, and performance optimization. Collaborate with engineering, analytics, governance, security, and business teams in an Agile, product-oriented environment with active AI-assisted development.

Leads the design and delivery of scalable infrastructure data systems, including ingestion pipelines, transformations, data models, and services for usage, cost, ownership, and planning. Establishes technical direction, data contracts, quality controls, monitoring, and operational processes while leading cross-functional initiatives and mentoring engineers. Uses AI responsibly to improve development and data-quality workflows while validating outputs and protecting sensitive information.