Top Remote Analysis Reporting Jobs in Birmingham, AL

Creates, analyzes, edits, and maintains GIS data supporting fiber and HFC network planning, design, construction, and regulatory map updates. Uses ArcGIS and ArcFM to manage geodatabases, spatial datasets, parcel data, route assets, and network schematics. Conducts map research, interprets technical records, supports GIS projects, develops mapping standards, and responds to internal requests. Collaborates with legal, market expansion, engineering, construction, and design teams while ensuring geospatial data quality and alignment with GIS best practices.

Own end-to-end data architecture, including ingestion, ETL, transformation, extracts, reporting, and dashboards. Lead DevOps and infrastructure for AI engineering systems, establish platform standards, and build reliable production infrastructure. Write and ship code, mentor engineers, and hire and lead a growing data and platform team. Partner with leadership to align architecture and platform investments with product, research, and business priorities.

Analyze frontline operations performance across specialists, queues, vendors, and sites. Identify root causes behind SLA, AHT, accuracy, and utilization changes; quantify impacts; monitor emerging issues; and provide actionable recommendations to operations leadership. Define requirements for specialist metrics and dashboards, collaborate with analytics and support teams, explain findings in business reviews, and use AI analytics tools to accelerate investigations.

Leads the full digital experience research lifecycle, including user interviews, testing, surveys, behavioral analysis, experimentation, and conversion optimization. Defines research and web measurement strategies, analyzes qualitative and quantitative data, builds dashboards and executive presentations, and translates findings into compelling data stories. Partners with marketing, technology, design, product, and development teams to improve global web experiences, while maintaining scalable research documentation and insight repositories.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

Lead design, build, and operate scalable Databricks/Delta Lake data pipelines and Kimball dimensional models using dbt. Manage governance with Unity Catalog, optimize performance and cost, operationalize ML with MLflow, and coordinate/quality-check offshore vendor engineering. Mentor engineers, uphold standards, and deliver trusted data products that power analytics, reporting, and MLOps workflows.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Build and operate platform infrastructure for product analytics, data processing, and ML systems. Responsibilities include event tracking pipelines, Databricks Bronze-to-Gold lakehouse layers, schema evolution, data contracts, CI validation, backfills, monitoring, feature computation, model pipelines, lineage, PHI policy enforcement, and self-service developer tooling. The role focuses on making data and ML changes safe, observable, reproducible, and accessible to engineers and subject-matter experts.

Analyze financial, operational, commercial, customer, and organizational performance metrics. Build dashboards, scorecards, and executive reports; synthesize data into actionable insights; support forecasting, scenario analysis, business planning, strategic initiatives, and executive decision-making through quantitative analysis and modeling.

Design, build, and scale data pipelines, ETL workflows, analytics infrastructure, and machine-learning data systems. Ensure data quality, security, monitoring, and reliability while optimizing storage and processing performance. Collaborate with engineering, product, and analytics teams on data requirements, modeling, schemas, and scalable infrastructure. The role also establishes data engineering best practices and supports a data-driven culture.