As part of the role your responsibilities include:
- Coordinate with Business Users, Product Owners, Business Engineers, and technology team to understand data analysis requirements. Lead Data Analysis and responsible for all Data related capabilities.
- Responsible to translate business requirements to AI/ ML based solution.
- Experience in building end to end model including with direct business impact data cleaning, data analytics, features engineering, model selection, ensemble methods, performance metrics, and visualization.
- Proven track record in designing, developing and deploying Machine Learning models that created business impact
- Coordinating on projects requiring data integration and science skills, connecting bank-wide datasets
- Working with teams from different business function and divisions to solve complex machine learning problem
- Responsible to ensure that AI/ ML solutions meets bank-wide ML modelling guidelines and standards
- Excellent academic background with advanced degree in Computer Science, Engineering, Mathematics, Statistics or related Field.
- Relevant experience in data, AI/ML modelling related capabilities.
- Solid programming skills in Python, R or Java with integrated data science, engineering and development background. Solid grasp and experience of working with SQL
- Experience of working with ML frameworks like TensorFlow, Pytorch, Keras, ScikitLearn, XGBoost, SparkML or similar.
- Proficient in general NN models like SVM, random forest, decision tree, neural networks, GLM.
- Partner management experience is required to effectively gather the requirements and handle the delivery of data science outcomes
- Proficient in investment banking domain, and financial services products/ customer data will be an advantage.
- Proficient in agile development practices
- Understanding of parallel capabilities on the cloud (AWS, GCP, Azure) is highly desirable