Machine Learning Engineer - (Python, Credit Risk) Jobs in USA, NJ, Rutherford | Rose International Job
Role details
Job location
Tech stack
Job description
This is 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, 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 a specific focus on credit risk management
You will have to have 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:
Lead and 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
Lead, 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
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Only those lawfully authorized to work in the designated country associated with the position will be considered.
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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.
Requirements
Bachelor's degree/University degree or equivalent experience in STEM
Preferred Education:
PhD or master's degree in computer science, Data Science, Statistics, Mathematics, Engineering or related field, 8-10+ years of industry experience as a data scientist, specializing in ML Modeling, Ranking, Recommendations, or Personalization systems
8-10+ 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
Benefits & conditions
National average IT Jobs average New Jersey average
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