Data Scientist - Python

Grow your career as a Data Scientist with an innovative global bank in Jersey City, NJ. Contract role with strong possibility of extension. Will require working a hybrid schedule 2-3 days onsite per week.Join one of the world's most renowned global banks and trusted brand with over 200 years of continuously evolving financial services worldwide. You will work alongside some of the smartest minds in the industry who are excited to share their knowledge and to learn from you.Contract Duration: 12+ MonthsRequired Skills & Experience 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 What You Will Be DoingWill be responsible for data extraction and data analysis from structured and unstructured sources. 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. Will address complex problems involving financial data with specific focus on credit risk management. Will use an open and adaptive mindset to learn new and advanced models in LLM and GenAI and bring in innovative solutions to complex business problems. 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. Will 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. Posted By: Melissa Klein #J-18808-Ljbffr

Created: 2025-03-12