Python/AI Engineer

Responsibilities

• This a development position for establishing and implementing new or revised applications and programs in the Technology team.
• As part of this role, you will be responsible for data extraction and data analysis from structured and unstructured sources.
• You will 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.
• You will have to address complex problems involving financial data with specific focus on credit risk management.
• You will have to have open and adaptive mindset to learn new and advanced models in LLM and GenAI and bring in innovative solutions to complex business problems.
• Develop plans and coordinate with teams for all analytical efforts.
• Manage deliverables in a 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 technology SDLC process.
• Implement features through the ML lifecycle (Development, Testing, Training, Production, Monitoring/Evaluation) to ensure scalability and reliability.

Required Skills

• Bachelor's degree/University degree or equivalent experience in STEM
• PhD or master's degree in computer science, Data Science, Statistics, Mathematics, Engineering or related field.
• 5+ years of industry experience as a data scientist, specializing in ML Modeling, Ranking, Recommendations, or Personalization systems.
• 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 Skills

• 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 and financial instruments and modeling