Required Education:

• Master's degree/bachelor's degree in computer science, Data Science, Statistics, Mathematics, Engineering or related field.

Required Qualifications/Skills/Experience:

• 5+ years of industry experience as a backend Python developer or data scientist.
• 5+ years of experience designing and developing scalable and reliable machine learning systems for training, inference, monitoring, and iteration
• Strong background of

ML/DL/LLM

algorithms, model architectures, and training techniques

• Proficiency in Python, SQL, Spark, PySpark, TensorFlow or other analytical/model-building programming languages
• Proficiency with tools and LLMs
• Ability to work independently and collaboratively within a team.

Preferred Qualifications/Skills/Experience:

• Experience in GenAI/LLMs projects
• Familiarity with distributed data/computing tools (e.g., Hadoop, Hive, Spark, MySQL)
• Background in financial business, like banking, risk management
• Should be familiar with capital markets, financial instruments and modeling

Overview:

• This is a development position for establishing and implementing new or revised applications and programs in the Technology team
• Responsible for data extraction and data analysis from structured and unstructured sources
• Develop systems to clean results to build predictive and prescriptive models and implement them in a production environment by partnering with technology and business partners
• Address complex problems involving financial data with a specific focus on credit risk management
• Requires an open and adaptive mindset to learn new and advanced models in LLM and GenAI and bring in innovative solutions to complex business problems

Job Duties:

• Develop plans and coordinate with teams for all analytical efforts
• Manage deliverables in an agile environment and maintain clear communication with all model stakeholders
• Present status, issues, and analytical findings to various audience groups like business, technology management, risk review, model governance, etc.
• Data modelling and cleaning from internal and external sources
• Build predictive and prescriptive models by manipulating and cleaning results
• Develop, manage, and deploy analytical solutions using Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs) to production systems using the SDLC process
• Implement features through the ML lifecycle (Development, Testing, Training, Production, Monitoring/Evaluation) to ensure scalability and reliability.
• Only those lawfully authorized to work in the designated country associated with the position will be considered.
• Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client's business needs and requirements.

•