Data Scientist

As a Data Scientist specializing in healthcare, you will be responsible for developing advanced predictive models and AI solutions for the US and global healthcare markets. Your main role will involve collaborating with product teams and stakeholders to define data sources, algorithms, and key performance indicators. Additionally, you will deploy machine learning models into production environments, build ETL pipelines, and ensure strong data governance practices. Key Responsibilities: - Develop high-performing predictive healthcare models using machine learning and artificial intelligence techniques such as statistical modeling, optimization, GLM, Decision Trees, Boosting, SVM, Regression, and Clustering. - Perform model training, hyperparameter tuning, and evaluation to validate and enhance healthcare data products. - Collaborate with product teams and stakeholders to define data sources, algorithms, and key performance indicators. - Deploy machine learning models into production environments and build ETL pipelines, data transformation, and scalable modeling workflows. - Monitor model performance, optimize continuously, and ensure HIPAA compliance and strong data governance practices. Qualifications Required: - 3+ years of experience in the healthcare domain with exposure to healthcare data. - 5-7 years of experience in building and deploying machine learning models in production. - Robust experience in machine learning algorithms, statistical modeling, and expertise in Python, R, Scala, Spark/PySpark, and H2O. - Experience in AWS, Google AI/ML Platform, Snowflake, and Databricks. - Hands-on experience with ETL, data pipelines, and big data environments. - Strong communication skills to effectively engage with both technical and non-technical audiences. - Bachelors Degree in a quantitative field or equivalent experience of 8-10 years. - Experience in Deep Learning/Neural Networks, Docker & Kubernetes-based model deployment, Airflow/KubeFlow, and a Masters Degree in Data Science/Statistics/Engineering would be a plus. - Experience with H2O or similar machine learning platforms is desirable. As a Data Scientist specializing in healthcare, you will be responsible for developing advanced predictive models and AI solutions for the US and global healthcare markets. Your main role will involve collaborating with product teams and stakeholders to define data sources, algorithms, and key performance indicators. Additionally, you will deploy machine learning models into production environments, build ETL pipelines, and ensure strong data governance practices. Key Responsibilities: - Develop high-performing predictive healthcare models using machine learning and artificial intelligence techniques such as statistical modeling, optimization, GLM, Decision Trees, Boosting, SVM, Regression, and Clustering. - Perform model training, hyperparameter tuning, and evaluation to validate and enhance healthcare data products. - Collaborate with product teams and stakeholders to define data sources, algorithms, and key performance indicators. - Deploy machine learning models into production environments and build ETL pipelines, data transformation, and scalable modeling workflows. - Monitor model performance, optimize continuously, and ensure HIPAA compliance and strong data governance practices. Qualifications Required: - 3+ years of experience in the healthcare domain with exposure to healthcare data. - 5-7 years of experience in building and deploying machine learning models in production. - Robust experience in machine learning algorithms, statistical modeling, and expertise in Python, R, Scala, Spark/PySpark, and H2O. - Experience in AWS, Google AI/ML Platform, Snowflake, and Databricks. - Hands-on experience with ETL, data pipelines, and big data environments. - Strong communication skills to effectively engage with both technical and non-technical audiences. - Bachelors Degree in a quantitative field or equivalent experience of 8-10 years. - Experience in Deep Learning/Neural Networks, Docker & Kubernetes-based model deployment, Airflow/KubeFlow, and a Masters Degree in Data Science/Statistics/Engineering would be a plus. - Experience with H2O or similar machine learning platforms is desirable.