Top Entry Level Data & Analytics Jobs in Lincoln, NE

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Entry-level Data Analyst supporting Performance & Analytics for care operations. Build, validate, and QA recurring reports and dashboards (Retool/BI tools), pull and clean payer, clinical, and operational data, investigate discrepancies, maintain workflows and reporting-ready datasets, and support ad-hoc analytical priorities.

Collects, consolidates, cleans, analyzes, and visualizes experimental data from analytical equipment, test rigs, and pilot plants. Performs statistical analysis, anomaly detection, experimental design support, equipment validation, and QA/QC activities. Presents findings to technical leadership, identifies process improvements, and helps extract actionable insights from structured and spectral data.

Develop and support healthcare IT data strategies, governance frameworks, analytics roadmaps, data quality initiatives, metadata management, and enterprise data integration. Coordinate data migration, legacy clinical data integration, and clinical viewer transition efforts. Collaborate with stakeholders on analytics requirements, support dashboards and reporting, advise leadership on performance metrics, and ensure compliance with privacy, security, and governance requirements.

Entry-level data engineering development program involving three rotations, cloud-native data platforms, batch and real-time pipelines, distributed systems, ETL/ELT, data modeling, AI platforms, and enterprise data products. Participants use AWS, Spark, Java, Python, SQL, Snowflake, Kafka, and related technologies while gaining experience with LLM architectures, APIs, microservices, and secure production deployments.

Conduct quality assurance evaluations, root-cause and data analysis, and progress reporting. Serve as an escalation contact and subject matter expert for quality processes, while supporting problem prevention and continuous improvement projects. The role requires strong communication, analytical, organizational, presentation, and decision-making skills, along with English and Mandarin proficiency and fintech experience.

Leads R&D data stewardship across metadata, cataloging, data products, profiling, quality, governance, and compliance. Uses Informatica, SQL, Databricks, Python, and PySpark to curate data, automate workflows, define quality controls, and resolve complex issues. Applies AI-assisted stewardship and semantic data concepts while collaborating with technical and business stakeholders. Coaches other stewards, supports audit readiness, and improves stewardship standards and operating practices.

Lead client-facing analytics implementations across Google Analytics 4, Adobe Analytics, and tag management systems. Responsibilities include designing measurement strategies, auditing digital ecosystems, managing tagging and consent platforms, developing data governance and privacy solutions, analyzing performance, aligning KPIs with business goals, presenting insights, supporting proposals, and improving internal analytics standards. Preferred experience includes server-side tagging, data clean rooms, customer data platforms, experimentation, CRM systems, and ETL tooling.

Own trade performance reporting, dashboards, scorecards, promotional ROI analysis, range review support, category insights, and sales projections for major retail customers. The role turns sales and shopper data into commercial recommendations, supports retailer presentations and new product launches, and collaborates with Sales, Marketing, Supply Chain, Demand Planning, and Finance. It requires strong Excel and presentation skills, commercial curiosity, attention to detail, clear communication, and the ability to manage multiple priorities.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.