Description

You will build and maintain data pipelines, develop machine learning models, and drive strategic decisions through advanced analytics in a production environment.

Responsibilities

• Design, develop, and validate ML models for classification, regression, clustering, and prediction tasks while ensuring accuracy, robustness, and fairness.
• Acquire access to diverse data sources (SQL, NoSQL, graph databases) and create repeatable data pipelines for structured, semi-structured, and unstructured data.
• Perform feature selection and engineering, applying statistical techniques like hierarchical clustering and PCA to prepare data and enhance model interpretability.
• Conduct controlled experiments (A/B testing) to evaluate hypotheses and quantify the impact of AI solutions on operations.
• Monitor production ML model health, recalibrate as needed, and collaborate with MLOps and data engineers to establish deployment best practices.

Required Skills

• 5+ years of experience in data science, machine learning, or AI/ML roles.
• Proficiency in SQL and NoSQL database systems for data acquisition and management.
• Experience with MLOps principles and collaborating with data engineers on production infrastructure.
• Strong background in statistical analysis, including PCA and hierarchical clustering.
• Ability to integrate domain knowledge into ML solutions for areas like care delivery, financial risk, or marketing.
• Skills in creating dashboards and interactive visualizations to communicate complex findings to diverse audiences.
• Experience mentoring junior analysts and leading cross-functional collaboration.
• Any Graduate degree.

Key Skills

Education

Any Gradute