Top Remote Artificial Intelligence Data & Analytics Jobs

Design, implement, and maintain dbt/Snowflake ELT transformations to convert raw clinical and multimodal health data into trusted, analysis-ready models; enforce data quality, lineage, testing, CI/CD, and documentation; collaborate with clinical and ML teams to harmonize ontologies and support de-identification and ETL across health systems.

Design, deploy, and govern enterprise-scale data architectures and platforms to support analytics and AI. Define modeling standards, integration pipelines, data quality, lineage, and security. Lead technical direction, mentor engineers, evaluate AI tooling, and support proofs of concept and solution roadmaps that enable generative AI and RAG solutions.

As a Data Engineer, you will design and maintain data infrastructure, build ingestion pipelines, and collaborate with ML and product teams for data-driven features.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Manage client risk and maximize margins by making +EV pre-match and in-play decisions. Monitor depth charts, research verified news, analyze betting trends, and convert data into quantifiable trading actions. Work flexible hours and collaborate with cross-functional teams to improve processes and profitability.

The Product Analyst will design experiments, analyze user behavior, and communicate insights to drive engagement and retention decisions effectively.

The role involves architecting intelligence infrastructure, building data pipelines, collaborating with other teams, and ensuring data accessibility and security for threat detection systems.

Own and cleanse payments data to produce accurate Power BI dashboards and forecasts. Analyze interchange, ACH, VCC, and check costs to identify margins and optimization opportunities. Deliver executive-level storytelling, perform rigorous reconciliations, and act as an internal consultant to guide resource allocation and reduce payment costs.

The Staff Product Analytics Engineer will enhance product data usage across teams by owning data infrastructure, creating tools for self-service data, and ensuring data-driven decisions. Responsibilities include collaborating with various teams to improve data insights and maintain data pipelines.

The Solution Engineer - Data Engineering Specialist will provide technical leadership in the financial services sector, collaborating with sales teams to demonstrate Snowflake's data platform capabilities while engaging with technical and executive stakeholders.