Python Software Engineer
Axelon, Jersey City, NJ, United States
Summary:
This is a development position for establishing and implementing new or revised applications and programs in the Technology team.
Responsibilities:
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 modeling 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 technology SDLC process.
Implement features through the ML lifecycle (Development, Testing, Training, Production, Monitoring/Evaluation) to ensure scalability and reliability.
Requirements:
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 in 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.
This is a development position for establishing and implementing new or revised applications and programs in the Technology team.
Responsibilities:
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 modeling 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 technology SDLC process.
Implement features through the ML lifecycle (Development, Testing, Training, Production, Monitoring/Evaluation) to ensure scalability and reliability.
Requirements:
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 in 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.