Top Analysis Reporting Jobs in Charleston, SC

Conducts research and outreach to collect official local election documents, processes election and candidate data, and maintains Ballotpedia’s database. Monitors election schedules, audits and cleans data, interprets election materials, researches election laws, and improves workflows and local election coverage. The role requires careful, organized, neutral research, collaboration, concise communication, and effective use of online productivity tools in a fully remote environment.

The Workday Reporting and Security Analyst develops and maintains Workday reports, dashboards, calculated fields, and People Analytics to deliver workforce insights. The role gathers reporting requirements, validates data, troubleshoots issues, conducts release testing, and documents solutions. It also administers Workday security roles and policies, audits access, enforces privacy and SOX controls, supports internal and external audits, and partners with HR, Finance, IT, vendors, and business stakeholders.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

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.

Own Hercules’ full data stack, including ETL from third-party providers into BigQuery, data modeling with dbt and medallion architecture, semantic-layer metric definition, and self-service business intelligence in Omni. Build reliable, maintainable systems and dashboards while applying strong software architecture, API design, code quality, and AI-assisted development practices.

Build and expand the company’s analytics data stack using Looker, LookML, dbt, BigQuery, and Airbyte. Develop data models, integrate multiple business systems, create KPI dashboards, and analyze product usage, customer health, adoption, and revenue data. The role empowers business teams with self-service analytics, actionable insights, and data-informed decision-making while developing a strong understanding of business metrics.

Conduct open-ended research on markets, companies, products, funding, competitors, technologies, people, and regulations. Transform findings into clear, sourced matrices, briefs, landscape maps, and one-pagers with actionable points of view. Use AI tools and lightweight scripts or scrapers to accelerate research, manage multiple shifting requests, and communicate concise conclusions to leadership.

Develops scalable data and software systems using Python and Apache Spark. Designs APIs, data models, ETL workflows, orchestration, and data interactions while optimizing performance, scalability, integrity, and security. Builds user interfaces, contributes to automated testing, applies Agile practices, and supports CI/CD delivery. The role requires strong software engineering, distributed computing, analytical, and communication skills, with AWS, R, Databricks, and SAS experience preferred.

Develop and optimize SQL Server and SSIS billing pipelines, automate data movement and validation with Python, and use R and Python for analytics, anomaly detection, and billing decision models. Build data-quality frameworks, support internal reporting tools, integrate ERP APIs, and collaborate with finance and operations stakeholders. The role requires maintainable, tested, auditable solutions and ownership of features across databases, pipelines, analytics, and internal applications.

Own marketing channel performance tracking, reporting, experimentation, dashboards, forecasting, and LTV analysis. Develop measurement frameworks, identify data issues, and translate complex findings into actionable recommendations for Marketing, Growth, Product, and Finance stakeholders. The role requires strong SQL, BI dashboarding, marketing measurement, experimentation knowledge, and effective analytical communication, with AI tools used to accelerate reporting and analysis.