Lead ML / Data Scientist

You will be responsible for designing and leading the development of various artificial intelligence initiatives aimed at improving the health and wellness of patients. Your role will involve defining the technical architecture to productize Innovaccer's machine-learning algorithms and bringing them to market through partnerships with different organizations. You should have a proven ability to break down complex business problems into machine learning problems and design solution workflows. Additionally, you will collaborate with the data platform and applications team to integrate data science capabilities or algorithms into their products/workflows. Working with development teams to create tools for repeatable data tasks that accelerate and automate the development cycle will also be part of your responsibilities. Key Responsibilities: - Define technical architecture for productizing machine-learning algorithms - Collaborate with data platform and applications team for seamless integration - Work with development teams to build tools for data tasks automation - Stay updated with advancements in AI and ML in the industry - Deploy production-ready models and provide interactive improvements - Implement deep learning techniques such as NLP and Computer Vision models - Utilize deep learning frameworks like Pytorch or Tensorflow - Develop and deploy models using ML platforms like Databricks, Azure ML, Sagemaker - Ensure global and local model explainability using techniques like LIME and SHAP Qualifications Required: - Masters in Computer Science, Computer Engineering, or relevant fields (PhD Preferred) - 7+ years of experience in Data Science (healthcare experience will be a plus) - Strong hands-on experience in Python for building enterprise applications - Expertise in deep learning techniques and classical ML algorithms - Experience deploying deep learning models at scale in production - Familiarity with ML platforms and model explainability techniques (Note: Additional details about the company were not provided in the job description.) You will be responsible for designing and leading the development of various artificial intelligence initiatives aimed at improving the health and wellness of patients. Your role will involve defining the technical architecture to productize Innovaccer's machine-learning algorithms and bringing them to market through partnerships with different organizations. You should have a proven ability to break down complex business problems into machine learning problems and design solution workflows. Additionally, you will collaborate with the data platform and applications team to integrate data science capabilities or algorithms into their products/workflows. Working with development teams to create tools for repeatable data tasks that accelerate and automate the development cycle will also be part of your responsibilities. Key Responsibilities: - Define technical architecture for productizing machine-learning algorithms - Collaborate with data platform and applications team for seamless integration - Work with development teams to build tools for data tasks automation - Stay updated with advancements in AI and ML in the industry - Deploy production-ready models and provide interactive improvements - Implement deep learning techniques such as NLP and Computer Vision models - Utilize deep learning frameworks like Pytorch or Tensorflow - Develop and deploy models using ML platforms like Databricks, Azure ML, Sagemaker - Ensure global and local model explainability using techniques like LIME and SHAP Qualifications Required: - Masters in Computer Science, Computer Engineering, or relevant fields (PhD Preferred) - 7+ years of experience in Data Science (healthcare experience will be a plus) - Strong hands-on experience in Python for building enterprise applications - Expertise in deep learning techniques and classical ML algorithms - Experience deploying deep learning models at scale in production - Familiarity with ML platforms and model explainability techniques (Note: Additional details about the company were not provided in the job description.)