Top Entry Level Data & Analytics Jobs

Reviews and prepares scientific datasets, metadata, documentation, and supplemental files for public archival publication through the Forest Service Research Data Archive. The role validates data quality, formats, accessibility, and compliance with metadata standards across tabular, geospatial, multimedia, database, and document formats. It also supports and trains researchers, coordinates delivery timelines, and assists with project collaboration.

Develops and maintains Power BI reports and analytics solutions, troubleshoots reporting issues, traces data through SQL and Databricks, and explains insights to nontechnical users. Advises customers and developers on BI and AI solutions, explores AI automation opportunities, recommends platform strategies, and provides training and best practices. The role requires advanced Power BI, DAX, SQL, Databricks, AI, and healthcare data knowledge, with Epic familiarity preferred.

Conducts primary and syndicated market research for advertisers and sales teams. Analyzes audience metrics, consumer insights, competitive advertising spend, targeting, marketplace trends, and advertising effectiveness. Creates data-driven presentations, fulfills ad-hoc research requests, supports project management, and educates marketing and sales staff on analytics. Requires strong analytical, communication, relationship-building, and multitasking skills, along with proficiency in Excel and PowerPoint.

Build workflow-specific data pipelines, integrations, and data models supporting AI solutions. Map data across systems, files, emails, and spreadsheets; transform unstructured documents into structured data; establish data quality checks; resolve data issues; and contribute reusable workflow data to the shared AI platform.

Develop interactive Power BI dashboards and automated reporting processes using existing databases. Analyze Institutional Review Board data to identify trends, performance metrics, workflow improvements, and actionable operational insights. Collaborate with stakeholders, manage multiple projects and deadlines, and support administrative or project-specific responsibilities. The role is hybrid, grant-funded through November 2027, and requires residence in New York, New Jersey, or Connecticut.

Executes scoped data engineering and software development tasks, supports client issue triage, onboarding, offboarding, monitoring, break-fix work, testing, documentation, and operational maintenance. Collaborates with senior engineers and cross-functional teams while using version control and AI-assisted development tools. The role is designed for an early-career professional building engineering fundamentals and gaining experience with production client systems and data pipelines.

Develops and maintains business intelligence reports, dashboards, metrics, data warehouses, and analytical solutions. Extracts and interprets financial and statistical data, ensures reporting accuracy and confidentiality, evaluates reporting needs, and supports business decision-making. The role also trains end users, collaborates with business intelligence teams, and creates recurring and ad hoc reports using SQL, Python, Tableau, and Power BI.

The BI Analyst partners with business and technology stakeholders to frame analytical questions, define KPIs, validate data, identify trends, and deliver actionable recommendations. The role develops dashboards, reports, visualizations, and custom extracts; investigates data quality issues; supports BI solution planning, testing, and delivery; and improves existing analytical products. It also includes stakeholder communication, user training, standards development, and guidance for team members.

Administer and configure Collibra to support enterprise data governance, metadata management, data catalogs, business glossaries, lineage, and governance workflows. Manage users, access controls, data quality, and stewardship processes; integrate Collibra with enterprise data platforms using APIs and connectors. Collaborate with architects, engineers, and business stakeholders to implement governance standards, with potential support for federal digital services engagements.

Build and maintain scalable SQL and Python ETL/ELT pipelines, Hive/Spark data warehouse workflows, orchestration processes, analytics-ready datasets, data quality checks, monitoring, backfills, and self-service reporting infrastructure. Partner with data scientists, analysts, architects, and operations stakeholders to support workforce, staffing, capacity, productivity, and operational reporting.