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Marquand

    Data Scientist with Reinforcement Learning - Indianapolis, United States - Katalyst Healthcares and Life Sciences

    Katalyst Healthcares and Life Sciences
    Katalyst Healthcares and Life Sciences Indianapolis, United States

    2 weeks ago

    Default job background
    Description
    Responsibilities:
    • Lead the design, development, and deployment of Reinforcement Learning algorithms and models to address complex business problems.
    • Collaborate with product managers, engineers, and other stakeholders to understand requirements and define project objectives.
    • Conduct thorough data analysis to identify patterns, trends, and opportunities for optimization.
    • Develop and maintain scalable RL frameworks and pipelines for training, evaluation, and inference.
    • Experiment with different RL techniques, architectures, and hyperparameters to improve model performance and efficiency.
    • Implement state-of-the-art RL algorithms and adapt them to specific use cases, considering factors such as scalability, interpretability, and robustness.
    • Work closely with software engineers to integrate RL solutions into production systems and ensure reliability and scalability.
    • Stay updated on the latest advancements in Reinforcement Learning research and apply them to real-world problems.
    • Mentor junior team members, provide technical guidance, and contribute to knowledge sharing within the organization.
    Requirements:
    • Bachelor's, Master's degree in Computer Science, Engineering, Mathematics, Statistics, or related field.
    • 6+ years of professional experience in data science, with a focus on Reinforcement Learning.
    • Solid understanding of machine learning fundamentals and deep learning techniques.
    • Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar.
    • Experience with RL libraries and frameworks (e.g., OpenAI Gym, Stable Baselines, RLlib).
    • Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
    • Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
    • Proven track record of delivering successful data science projects from conception to deployment.
    • Publications or contributions to the RL community (e.g., research papers, open-source projects) are a plus.


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