Lead end-to-end data science engineering projects, leveraging machine learning, big data pipelines, and generative AI (Artificial Intelligence) to solve business problems. Deliver key insights from business impact and statistical analysis to executive leadership, providing strategic guidance and actionable recommendations that drive business strategy and inform decision-making. Present complex technical findings and insights to both technical and non-technical stakeholders, translating data analysis into clear, actionable recommendations that inform business decisions. Collaborate closely with both internal teams, including data engineers, software engineers, product managers, and external suppliers, to integrate solutions into production systems and ensure alignment with business objectives. Manage agile development processes and ensure clear communication and collaboration between technical and non-technical stakeholders. Oversee project timelines and deadlines, driving timely delivery while ensuring continuous improvement throughout the development cycle. Architect and design scalable data pipelines to support machine learning workflows, ensuring high data quality, accessibility, and optimization for analysis. Evaluate emerging trends, techniques, and technologies in data science, machine learning, and artificial intelligence to ensure the team is using state-of-the-art methods and tools. Utilize: Python, SQL, Apache Spark, Apache Kafka, Machine Learning Frameworks, Application Architect, Project Management.
Required: Bachelor's degree or equivalent in Computer Science, Mathematics, Software Engineering or related and two (2) years of experience as a Data Engineer or related. Two (2) years of experience must include utilizing Python, SQL, Apache Spark, Apache Kafka, Machine Learning Frameworks, Application Architect, Project Management.
Please send resumes to [email protected]. Applicants must reference H257 in the subject line.
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