Senior Data Scientist

As a Data Scientist at Optum, a global organization dedicated to improving health outcomes through technology, your role will involve the following responsibilities: - Lead end-to-end development of machine learning and AI solutions, from problem definition to production deployment - Collaborate with cross-functional teams to identify business opportunities and translate them into data-driven solutions - Build, optimize, and maintain scalable data pipelines and ML models using modern data science and MLOps practices - Perform advanced analytics, feature engineering, and statistical modeling to derive actionable insights - Develop and implement NLP, LLM, time-series, or deep learning models as required by business use cases - Ensure model performance, quality, and stability through monitoring, retraining strategies, and experimentation - Mentor junior data scientists/analysts and contribute to best-practice standards for modeling, coding, and documentation - Communicate technical results effectively to leadership through dashboards, visualizations, and presentations - Partner with engineering teams to productionize models using CI/CD, MLflow, and cloud ML platforms - Drive innovation by researching and evaluating new AI technologies, frameworks, and methodologies Qualifications required for this role include: - B-Tech CSE graduate - Post-graduation in Statistics/Mathematics or any related subject - Data science certification - 5+ years of hands-on experience in data science, machine learning, and advanced analytics - 5+ years of experience building and deploying production-grade ML models (classification, regression, NLP, forecasting) - Expert-level proficiency in Python and SQL, with ML/DL libraries (e.g., Scikit-learn, TensorFlow, PyTorch) with 5+ years of experience - 2+ years of experience working with big-data technologies such as PySpark/Spark or distributed data platforms - 2+ years of experience with cloud platforms (Azure, AWS, or GCP) for model training and deployment - 2+ years of experience implementing MLOps (MLflow, CI/CD, model monitoring, data drift checks) - Experience mentoring or leading teams of data scientists or analysts for 2+ years - Proven track record of delivering at least 3-5 high-impact ML/AI solutions in production environments - Demonstrated ability to work with cross-functional stakeholders and present complex findings to non-technical audiences - Proven solid data storytelling abilities, demonstrated through executive-level presentations, dashboards, and narrative-driven insights that influenced key decisions Preferred Qualification: - Hands-on experience in GEN AI At Optum, you will be part of a culture guided by inclusion, talented peers, comprehensive benefits, and career development opportunities. Join us in advancing health optimization on a global scale and making a positive impact on the communities we serve. As a Data Scientist at Optum, a global organization dedicated to improving health outcomes through technology, your role will involve the following responsibilities: - Lead end-to-end development of machine learning and AI solutions, from problem definition to production deployment - Collaborate with cross-functional teams to identify business opportunities and translate them into data-driven solutions - Build, optimize, and maintain scalable data pipelines and ML models using modern data science and MLOps practices - Perform advanced analytics, feature engineering, and statistical modeling to derive actionable insights - Develop and implement NLP, LLM, time-series, or deep learning models as required by business use cases - Ensure model performance, quality, and stability through monitoring, retraining strategies, and experimentation - Mentor junior data scientists/analysts and contribute to best-practice standards for modeling, coding, and documentation - Communicate technical results effectively to leadership through dashboards, visualizations, and presentations - Partner with engineering teams to productionize models using CI/CD, MLflow, and cloud ML platforms - Drive innovation by researching and evaluating new AI technologies, frameworks, and methodologies Qualifications required for this role include: - B-Tech CSE graduate - Post-graduation in Statistics/Mathematics or any related subject - Data science certification - 5+ years of hands-on experience in data science, machine learning, and advanced analytics - 5+ years of experience building and deploying production-grade ML models (classification, regression, NLP, forecasting) - Expert-level proficiency in Python and SQL, with ML/DL libraries (e.g., Scikit-learn, TensorFlow, PyTorch) with 5+ years of experience - 2+ years of experience working with big-data technologies such as PySpark/Spark or distributed data platforms - 2+ years of experience with cloud platforms (Azure, AWS, or GCP) for model training and deployment - 2+ years of experience implementing MLOps (MLflow, CI/CD, model monitoring, data