Sr Data Science Software Engineer - NLP

Summary: Rocket's Data Modernization Business Unit aids customers in managing, governing, and maximizing the value of their enterprise data assets. Our clientele comprises many Fortune 500 companies, including some of the world's largest banks, insurance companies, and manufacturing organizations. We are currently seeking motivated and innovative individuals to join our applied machine learning team. This is an opportunity to play a crucial role in the continued evolution of our world-class solutions. Data Scientist is a highly motivated and experienced individual proficient in advanced machine learning models, particularly language models, document understanding and analysis, and code generation. They will be responsible for understanding and adapting current research. The position requires a deep understanding of computational linguistics, image processing, and Python programming. The selected candidate will be part of a collaborative team dedicated to building, fine-tuning, and deploying state-of-the-art models to solve real-world problems in information management, data intelligence, content automation, audit, and analytics. This presents an opportunity to create tremendous business value as we assemble a world-class applied machine learning team. Essential Duties and

: • Consult with key internal and external stakeholders to understand and frame model

and potential applications. • Design, develop, and deploy machine learning models using tools and platforms optimized for distributed machine learning. • Recommend ongoing improvements to methods and algorithms that lead to findings, including new information. • Evaluate the applicability of current research to our problem domain and software solutions. • Collaborate closely with software engineers to integrate the trained models into end-user applications. • Develop sound analytic plans based on available data sources, business partner needs, and required timelines. • Manage deliverables across multiple projects in a deadline-driven environment and projects related to a wide variety of business settings. • Present results, insights, and recommendations to both technical and non-technical stakeholders.