Data Scientist

• 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.

• 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.®

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