Design and lead the development of various artificial intelligence initiatives to help improve health and we'llness of patients
Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them.
Define technical architecture to productize Innovaccer s machine-learning algorithms and take them to market with partnerships with different organizations
Proven ability to break down complex business problems into machine learning problems and design solution workflows.
Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows.
Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle.
Define and execute on the quarterly roadmap
What You Need
Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred)
7+ years of experience in Data Science (healthcare experience will be a plus)
Strong written and spoken communication skills
Strong hands-on experience in Python - building enterprise applications alongwith optimization techniques.
Strong experience with deep learning techniques to build NLP/Computer vision models as we'll as state of art GenAI pipelines - knowledge of implementing agentic workflows is a plus.
Has demonstrable experience deploying deep learning models in production at scale with interactive improvements- would require hands-on expertise with at least 1 deep learning frameworks like Pytorch or Tensorflow.
Has keen interest in research and stays updated with key advancements in the area of AI and ML in the industry.
Deep understanding of classical ML techniques - Random Forests, SVM, Boosting, Bagging - and building training and evaluation pipelines.
Demonstrate experience with global and local model explainability using LIME, SHAP and associated techniques.
Hands on experience with at least one ML platform among Databricks, Azure ML, Sagemaker s
Experience in developing and deploying production ready models
Knowledge of implementing an MLOps framework.
Possess a customer-focused attitude through conversations and documentation
