Machine Learning Engineer

S&P Global•New York, NY

14d•Hybrid

About The Position

Kensho Technologies LLC seeks a Machine Learning Engineer who will identify, research, prototype, and build predictive data-driven products based on statistical analysis and machine learning. Conduct original research and data analysis on large proprietary and open-source data sets to identify interesting patterns, associations, correlations, outliers, and anomalies. Formulate and test hypotheses about the distributions and regularities underlying the data. Design, implement, and evaluate statistical and machine learning models for explaining and predicting patterns in vast amounts of financial data, including financial documents. Write production code implementing predictive models and algorithms. Write tests to ensure the robustness and reliability of productionized models. Conduct peer review of research, prototypes, models, and code. Remain current in the theory and application of statistical and machine learning techniques. Maintain and acquire expertise with tools and packages for numerical and statistical programming, data analysis, and machine learning modeling.

Requirements

Master’s degree in Computer Science, Statistics, Data Science, or related quantitative field plus one (1) year of experience in data science or a related quantitative occupation.
One (1) year of experience must include: Machine Learning (ML) and artificial intelligence (AI) tools
Data Preprocessing, Exploration and Visualization tools, including Jupyter, Matplotlib, Pandas, Scikit-learn
Data Management and Storage tools
Deployment and Machine Learning operations
Conducting and publishing Machine Learning research and producing code
Agentic systems, including Large Language Model (LLM) code generation and tool utilization.

Responsibilities

Identify, research, prototype, and build predictive data-driven products based on statistical analysis and machine learning.
Conduct original research and data analysis on large proprietary and open-source data sets to identify interesting patterns, associations, correlations, outliers, and anomalies.
Formulate and test hypotheses about the distributions and regularities underlying the data.
Design, implement, and evaluate statistical and machine learning models for explaining and predicting patterns in vast amounts of financial data, including financial documents.
Write production code implementing predictive models and algorithms.
Write tests to ensure the robustness and reliability of productionized models.
Conduct peer review of research, prototypes, models, and code.
Remain current in the theory and application of statistical and machine learning techniques.
Maintain and acquire expertise with tools and packages for numerical and statistical programming, data analysis, and machine learning modeling.