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# Data Scientist

- **Company:** Robert Half
- **Location:** Dover, DE, United States
- **Contract:** Temporary contract
- **Skills:** Business Analytics Applications, Big Data, Information Engineering, Extract Transform Load (ETL), Distributed Computing Environment, Apache Hadoop, Python (Programming Language), Data Streaming, Apache Spark, Data Analytics, Apache Kafka
- **Published:** October 23, 2026
- **Apply:** https://dejobs.org/x/x/DE113AD027C041638A1FC8ABF2C66342/job/

## About the Role

* Document methodologies, assumptions, and results clearly so that technical and non-technical stakeholders can understand key findings. Requirements * Hands-on experience with Python for data analysis, modeling, and data engineering tasks.

 * Strong working knowledge of Apache Spark for distributed data processing and large-scale analytics.

 * Experience using Apache Hadoop technologies in data-intensive environments.

 * Familiarity with Apache Kafka for ingesting and processing streaming data.

 * Proven ability to build and support ETL processes for structured and unstructured data sources.

 * Background in data science, analytics, or a related technical discipline with the ability to solve complex data problems.

 * Ability to communicate technical concepts and analytical insights effectively to diverse stakeholders. Technology Doesn't Change the World, People Do.®

## Description

* Design and maintain data pipelines that collect, transform, and prepare large datasets for analytical and operational use.

 * Develop statistical models and data-driven solutions that help identify trends, improve forecasting, and support business strategy.

 * Use Python and distributed processing tools to analyze high-volume data efficiently and produce meaningful recommendations.

 * Work with Spark and Hadoop-based environments to manage large-scale data processing and support advanced analytics workloads.

 * Integrate streaming and batch data from multiple sources, including Kafka, to ensure timely and accurate data availability.

 * Partner with cross-functional teams to translate business questions into analytical approaches, technical requirements, and measurable outcomes.

 * Build ETL workflows that improve data quality, consistency, and accessibility across reporting and analytical platforms.