equired Skills and Experience:
- Minimum 8 years of hands-on experience in machine learning, artificial intelligence, or data science roles.
- Demonstrated experience in the banking or finance sector, with a strong understanding of regulatory compliance.
- Advanced programming proficiency in Python, R, or Scala.
- Expertise in leading ML libraries and frameworks: TensorFlow, PyTorch, Scikit-learn.
- Experience working with big data technologies such as Hadoop and Spark.
- Solid knowledge of SQL and/or NoSQL database systems.
- Background in risk modeling, capital models, and regulatory frameworks relevant to banking.
- Practical experience with ML ops tools (Docker, Kubernetes, MLflow, Kubeflow, Airflow).
- Strong skills in statistical modeling, optimization techniques, and feature engineering.
- Exceptional ability to communicate technical concepts and results to non-technical audiences.
Key Responsibilities:
- Lead end-to-end machine learning projects, from problem definition through deployment and monitoring.
- Design, develop, and implement robust predictive models and risk modeling frameworks for banking and capital management.
- Collaborate with data engineers, analysts, and business units to identify opportunities for machine learning applications.
- Ensure all ML solutions comply with industry regulations and internal risk management standards.
- Oversee the operationalization of models using ML ops tools (Docker, Kubernetes, MLflow, Kubeflow, Airflow).
- Present findings, model outcomes, and recommendations clearly to non-technical stakeholders and senior management.
- Mentor junior team members and foster best practices in statistical modeling, feature engineering, and optimization.
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.