VP - Data Scientist (AI/ML Lead)

You will collaborate with all Asset and Wealth Management lines of business and functions to deliver machine learning solutions. You will analyze data, identify patterns, and visualize outcomes while working iteratively with business to experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant technology and business impact. Key responsibilities: - Analyze data, identify patterns, and visualize outcomes - Experiment, develop, and productionize high-quality machine learning models, services, and platforms - Collaborate with all Asset and Wealth Management lines of business and functions - Work iteratively with business to deliver machine learning solutions - Utilize solid programming skills in R or Python - Apply deep knowledge in Machine Learning, Data Mining, Information Retrieval, and Statistics - Expertise in Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis - Knowledge of machine learning frameworks such as Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, and Scikit-Learn - Demonstrate strong analytical and critical thinking skills - Possess self-motivation, excellent communication skills, and be a team player Qualifications required: - BS, MS, or PhD degree in Computer Science, Statistics, Mathematics, or a Machine learning related field - Solid programming skills in R or Python (preferred) - Deep knowledge in Machine Learning, Data Mining, Information Retrieval, and Statistics - Expertise in at least one of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis - Knowledge of machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, and Scikit-Learn - Strong analytical and critical thinking skills - Self-motivation, great communication skills, and the ability to work well in a team Preferred qualifications: - Experience of working in financial services - Major in finance in undergrad/postgrad or professional qualification like CFA is a major plus - Knowledge of cloud computing platforms such as Google Cloud, Amazon Web Service, Azure, Docker, Kubernetes - Experience in big data technologies such as Hadoop, Hive, Spark, Kafka (Note: Omitted additional details of the company from the job description) You will collaborate with all Asset and Wealth Management lines of business and functions to deliver machine learning solutions. You will analyze data, identify patterns, and visualize outcomes while working iteratively with business to experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant technology and business impact. Key responsibilities: - Analyze data, identify patterns, and visualize outcomes - Experiment, develop, and productionize high-quality machine learning models, services, and platforms - Collaborate with all Asset and Wealth Management lines of business and functions - Work iteratively with business to deliver machine learning solutions - Utilize solid programming skills in R or Python - Apply deep knowledge in Machine Learning, Data Mining, Information Retrieval, and Statistics - Expertise in Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis - Knowledge of machine learning frameworks such as Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, and Scikit-Learn - Demonstrate strong analytical and critical thinking skills - Possess self-motivation, excellent communication skills, and be a team player Qualifications required: - BS, MS, or PhD degree in Computer Science, Statistics, Mathematics, or a Machine learning related field - Solid programming skills in R or Python (preferred) - Deep knowledge in Machine Learning, Data Mining, Information Retrieval, and Statistics - Expertise in at least one of the following areas: Natural Language Processing, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis - Knowledge of machine learning frameworks: Tensorflow, Caffe/Caffe2, Pytorch, Keras, MXNet, and Scikit-Learn - Strong analytical and critical thinking skills - Self-motivation, great communication skills, and the ability to work well in a team Preferred qualifications: - Experience of working in financial services - Major in finance in undergrad/postgrad or professional qualification like CFA is a major plus - Knowledge of cloud computing platforms such as Google Cloud, Amazon Web Service, Azure, Docker, Kubernetes - Experience in big data technologies such as Hadoop, Hive, Spark, Kafka (Note: Omitted additional details of the company from the job description)