Applied Artificial Intelligence Machine Learning, Associate
4 days ago
The Corporate Technology Data Science and AI organization solves challenging business problems using data science and machine learning techniques across Corporate Technology and the supported Corporate Functions
As a Machine Learning Associate in this team, you will build effective, scalable, and modern analytical solutions for various banking domain problems and deploy them into production business workflows. This is an exciting opportunity to work alongside a world-class group of Data Scientists and Machine Learning Engineers and have profound influence on the business and technology processes of the firm. You will have broad areas of ownership including but not limited to stakeholder engagement, data mining, insights delivery, training and deployment of machine learning/LLM solutions as well as the ability to influence entire organizations. All in a modern data and development environment.
Job Responsibilities
- Develop and implement of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.
- Design, deploy, and manage of prompt-based models on LLMs for various NLP tasks in the financial services domain.
- Conduct and guide research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
- Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.
- Communicate effectively with both technical and non-technical stakeholders, including senior leadership.
- Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
- Develop and maintain tools and frameworks for prompt-based model training, evaluation, and optimization.
- Analyze and interpret data to evaluate model performance and identify areas of improvement.
Required Qualifications, Capabilities, And Skills
- Master's degree in a data science-related discipline, plus at least three years of industry experience (or: PhD in a data science-related discipline)
- Extensive experience with data analysis and transformation (especially in Python) and analytics
- Experience with continuous integration models and unit test development
- Strong written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- Curious, hardworking and detail-oriented, and motivated by complex analytical problems
Preferred Qualifications, Capabilities, And Skills
- Familiarity with the financial services industry
- Experience with A/B testing and data/metric-driven product development, cloud-native deployment in a large-scale distributed environment and ability to develop and debug production-quality code
- Some industry experience in implementing machine learning as well as deep learning toolkits (e.g. TensorFlow, PyTorch, Scikit-Learn)
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