Ai Data Science Engineer
Insight Global
Job Descriptione 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.
Key Responsibilities
Design, build, and productionize AI and machine learning models.
Develop AI agents and agentic workflows using modern LLM frameworks.
Build solutions supporting commercial underwriting and prospect scouting.
Apply traditional machine learning, deep learning, and graph-based modeling techniques to complex business problems.
Develop and optimize models using Python and PySpark.
Work with graph neural networks / graph-based machine learning where appropriate.
Build agentic AI solutions using LangChain and LangGraph within AWS environments.
Take high-level or abstract business concepts and translate them into mathematical, analytical, and technical solutions.
Partner with business and technical stakeholders to move AI solutions from concept ->
model development ->
production.
Evaluate model performance and continuously improve AI/ML solutions.
Skills and Requirements
Must-Have Skills2+ 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.
Banking experince
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to View email address on ca.hrm.tc.
#J-18808-Ljbffr
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.
Key Responsibilities
Design, build, and productionize AI and machine learning models.
Develop AI agents and agentic workflows using modern LLM frameworks.
Build solutions supporting commercial underwriting and prospect scouting.
Apply traditional machine learning, deep learning, and graph-based modeling techniques to complex business problems.
Develop and optimize models using Python and PySpark.
Work with graph neural networks / graph-based machine learning where appropriate.
Build agentic AI solutions using LangChain and LangGraph within AWS environments.
Take high-level or abstract business concepts and translate them into mathematical, analytical, and technical solutions.
Partner with business and technical stakeholders to move AI solutions from concept ->
model development ->
production.
Evaluate model performance and continuously improve AI/ML solutions.
Skills and Requirements
Must-Have Skills2+ 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.
Banking experince
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to View email address on ca.hrm.tc.
#J-18808-Ljbffr
Vacancy posted 52 minutes ago
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