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.

Education

Any Gradute