Top Remote Data & Analytics Jobs in Kansas City, MO

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

The role oversees analytical characterization and comparability studies for biologics, ensuring regulatory compliance and leadership in product development.

As a Data Scientist, you will analyze blockchain data to derive insights, develop and deploy predictive models, and improve product offerings.

Lead Alpaca's data department, managing 15 team members across Platform Engineering, Analytics Engineering, and Data Science. Oversee data strategy, operational delivery, and architecture decisions, ensuring alignment with business needs and cost management.

As a Data Engineer, you will build and maintain data pipelines, convert data into metrics, and operate the platform on AWS. Responsibilities include writing production code, processing data from APIs, and enhancing the orchestration layer using Dagster, while ensuring compliance in a HIPAA-regulated environment.

The VP Global Grid Modeling will lead global data strategy, manage high-performing teams, ensure quality datasets, and engage with customers for insights in energy markets.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

The Marketing Data Scientist will analyze data, onboard clients, develop data pipelines in R, and propose improvements to enhance efficiency.

As a Senior Forward Deployed Data Engineer, you will design and implement data pipelines for media agency clients, manage technical delivery, and ensure data security while mentoring junior engineers and communicating effectively with stakeholders.

Design, build, and maintain data models, pipelines, and access layers to support care delivery, operations, and analytics. Ensure data quality, governance, and reliability while optimizing infrastructure and performance. Serve as a technical leader, review code, set engineering best practices, and collaborate cross-functionally to translate business needs into scalable data solutions.