As a Vice President, Applied AI/ML Lead in our technology team, you will leverage your expertise in machine learning, natural language processing, and deep learning to address complex challenges in commercial banking and financial services. You will work collaboratively with a team that values innovation and creativity, using your skills to develop and deploy machine learning models that drive business success.
Job Responsibilities:
- Build and train production-grade ML models on large-scale datasets for commercial banking use cases.
- Utilize data processing frameworks like Spark and AWS EMR for feature engineering with structured and unstructured data.
- Apply deep learning models such as CNN, RNN, and NLP (BERT) for tasks like entity resolution, forecasting, and anomaly detection.
- Build ML models across public and private cloud environments, including Kubernetes.
- Create end-to-end ML pipelines to transform applications and business processes into AI systems.
- Develop batch and real-time model prediction pipelines integrated with existing applications.
- Collaborate on large-scale data modeling experiments, evaluating against baselines, and extracting key insights.
Required qualifications, capabilities, and skills:
- 6+ years of experience as a Data Scientist.
- Advanced degree in Computer Science, Data Science, or a related field.
- Expertise in Python, PySpark, deep learning frameworks like TensorFlow, and MLOps.
- Experience designing and deploying scalable distributed ML models in production.
- Proficiency in analytics tools such as SQL, Presto, Spark, Python, and AWS suite.
- Familiarity with machine learning techniques and advanced analytics.
Preferred qualifications, capabilities, and skills:
- Experience with end-to-end pipelines using frameworks like KubeFlow and TensorFlow.
- Experience with crowd-sourced data labeling is a plus.