Top Data & Analytics Jobs in Charleston, SC

Support GiveWell research by quality-checking and updating cost-effectiveness models, conducting desk research, summarizing grantee monitoring and evaluation, writing clear public summaries, and performing ad-hoc high-impact projects and project-management support for research investigations.

Design and maintain company-wide dashboards, define KPI frameworks, implement tracking and data governance, write advanced SQL, partner with product and engineering, build predictive/AI-ready data layers, automate reporting, and present insights to leadership to drive operational and financial improvements.

The Senior Data Engineer will scale and evolve the data platform, develop ETL/ELT pipelines, establish best practices, and optimize systems for performance while collaborating with various teams.

The Data Engineer is responsible for designing data workflows and pipelines, implementing systems engineering principles, and deploying data streaming technologies while ensuring compliance with industry regulations and best practices.

The Sr. Data Engineer - Databricks designs and maintains scalable data solutions using Apache Spark and Databricks, ensuring data quality and performance for analytics and reporting.

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.

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

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.