Data Scientist

Malvern, Pennsylvania

 RIT Solutions, Inc.
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Data Scientist
hybrid - Malvern pa -

Key Responsibilities:
  • Develop, implement, and maintain robust machine learning models using GenAI agentic framework.
  • Engage in prompt engineering to optimize the interaction with large language models, with other AI systems or tools.
  • Utilize techniques like Retrieval-Augmented Generation (RAG) to enhance AI solutions with real-time information retrieval.
  • Develop and design graph databases using tools such as NetworkX or AWS Neptune for relationship-oriented data modeling.
  • Fine-tune Large Language Models (LLMs) to tailor solutions to specific business needs and improve model efficiency.
  • Leverage AWS services (including S3, ECS, ECR, Lambda, SageMaker, and more) to build scalable machine learning solutions.
  • Utilize data engineering skills with Glue and PySpark for efficient data preparation and processing.
  • Conduct model evaluation and testing to ensure accuracy, reliability, and robustness.
  • Monitor machine learning models in production, implementing strategies for ongoing performance tracking and optimization.
  • Ensure the security of models and data through secure API integration, utilizing tokens and comprehensive data security principles.
  • Govern models in compliance with the Machine Learning Development Lifecycle (MDLC) and Machine Learning Production Lifecycle (MPLC) processes.
  • Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders, to deliver impactful machine learning solutions.
  • Stay up-to-date with the latest advancements in machine learning, generative AI technologies, and methodologies.
Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Data Science, or a related field.
  • 5+ years of experience in machine learning and data engineering roles.
  • Experience with prompt engineering and fine-tuning large AI models.
  • Familiarity with Retrieval-Augmented Generation (RAG) techniques.
  • Proficiency in designing graph databases using tools like AWS Neptune, Neo4J or NetworkX.
  • Proficiency in Python, with a strong understanding of libraries such as TensorFlow, PyTorch, and Scikit-learn.
  • Extensive experience with AWS services relevant to machine learning, including SageMaker, Glue and PySpark.
  • Experience with secure API integration and a solid understanding of data security practices.
  • Strong understanding of data preprocessing, feature engineering, and model training/evaluation.
  • Experience with model monitoring, performance analysis, and optimization techniques.
  • Familiarity with model governance frameworks, including MDLC and MPLC processes.
Date Posted: 05 May 2025
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