A leading national financial services institution is seeking a Machine Learning Engineer to build scalable data solutions and deploy ML models that enhance decision-making across the organization.
Requirements
- Advanced knowledge of Python and SQL
- Experience with data visualization tools such as Tableau or Power BI
- Hands-on experience with ETL/ELT pipeline development
- Familiarity with ML frameworks like scikit-learn, pandas, NumPy
- Experience working with cloud-based data platforms (GCP, AWS, Azure)
- Exposure to MLOps practices including CI/CD pipelines and containerization (Docker, Kubernetes)
Responsibilities
- Design, build, and deploy production-ready machine learning models that address real business problems and drive operational efficiency.
- Create and manage robust, scalable data pipelines for ETL/ELT processes using SQL and Python, ensuring high data quality and accessibility.
- Partner with data scientists, analysts, and business stakeholders to define requirements and translate them into actionable technical deliverables.
- Create compelling and informative dashboards using tools like Tableau or Power BI to communicate insights and track performance metrics.
- Monitor, evaluate, and refine deployed models to ensure sustained performance and adapt to changing business needs.
Other
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related discipline (or equivalent experience)
- 3+ years in a data engineering, machine learning, or data science role
- Excellent problem-solving skills and ability to communicate technical concepts to non-technical stakeholders
- Must be comfortable working remotely and available during Eastern Time business hours
- Master’s degree in a relevant field
- Previous experience in financial services or highly regulated environments
