Opens LinkedIn
- Employment type
- Contract
- Experience level
- Mid-level · 2+ years
- Posting language
- English
- Working hours
- 40 hours per week
- Office presence
- 3 days per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available
Job summary
Translate ambiguous Commercial Banking and underwriting business problems into structured mathematical or data science problems, then develop appropriate AI and machine learning models. Help productionize advanced AI/ML solutions, including agentic AI applications.
Job details
12 Month Contract with extensions 3 days on site - Potential for fully remote Hourly Rate: $80-95/hr T4A Job Description: We are seeking an AI Data Science Engineer to join a team focused on developing and productionizing advanced AI and machine learning solutions for Commercial Banking and underwriting. This is a hybrid Data Scientist + AI/ML Engineer role. The ideal candidate can take an ambiguous business problem, translate it into a mathematical/data science problem, build the appropriate model, and then help bring that solution into production. Required Skills & Experience: 2+ years of hands-on Data Science, Machine Learning, or AI Engineering experience. Strong hands-on Python development experience. Experience building machine learning models from scratch. Strong understanding of traditional ML methodologies. Experience with deep learning. Hands-on experience building and productionizing AI/ML models. Experience with PySpark for large-scale data processing. Experience with scikit-learn or comparable Python ML libraries. Experience building AI agents / agentic AI solutions. Strong experience with LangChain and/or LangGraph. Experience developing AI/ML solutions within AWS. Strong problem-solving and critical-thinking skills, especially the ability to translate an abstract business problem into a structured mathematical or ML problem. Nice to Have Skills & Experience Banking experience “Artificial intelligence tools are used to assist in screening and assessing applicants for this position." Vacancy: This posting is for a currently vacant role, and the successful candidate will be hired into an existing open position.
What you’ll do
Translate ambiguous Commercial Banking and underwriting business problems into structured mathematical or data science problems, then develop appropriate AI and machine learning models. Help productionize advanced AI/ML solutions, including agentic AI applications.
Requirements
Requires at least 2 years of hands-on experience in data science, machine learning, or AI engineering, with strong Python skills and experience building models from scratch. Candidates should have experience with traditional and deep learning, productionizing models, PySpark, scikit-learn or comparable libraries, AI agents using LangChain or LangGraph, and AWS; banking experience is a plus.
Listed skills
- Problem solving · Preferred
- Machine learning · Preferred
- Critical Thinking · Preferred
- Amazon Web Services · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- Data Science
- Machine Learning
- Artificial Intelligence
- Deep Learning
- PySpark
- Scikit-Learn
- AI Agents
- Agentic AI
- LangChain
- LangGraph
- AWS
- Model Productionization
- Problem-Solving
- Critical Thinking
- Commercial Banking
Job areas
- Data & Analytics
- Technology
- Software
- Science & Research
- Finance & Accounting
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