Position Description:

Leads initiatives involving extensive multi-dimensional databases, complex business infrastructure, and collaboration with cross-functional teams. Performs large-scale data preprocessing, manipulation, and analytical tasks. Develops supervised and un-supervised Machine Learning (ML) algorithms (regression, decision trees, random forest, and neural networks). Designs and implements Natural Language Processing (NLP) solutions, including the use of Large Language Models (LLMs) and generative Artificial Intelligence (AI), to enhance text understanding and generation capabilities. Researches and builds sophisticated, innovative, and scalable AI algorithms, models, and platforms to improve customer experience and drive business outcomes.

Primary Responsibilities:

• Identifies business opportunities and evaluates best approaches for predictive or prescriptive analytics.

• Gathers internal and external data (structured or unstructured) from multiple sources using programming languages.

• Implements best practices for model development, iteration, and code management.

• Conducts code reviews.

• Draws key business insights from advanced quantitative analyses and presents findings to broader audience and senior management.

• Supports junior team members in learning data sources, tools, and technologies.

• Develops and implements a set of techniques or analytics applications to transform raw data into meaningful information, using data-oriented programming languages and visualization software.

• Applies data mining, data modeling, natural language processing, and machine learning for extracting and analyzing information from large structured and unstructured datasets.

• Visualizes, interprets and reports data findings.

Education and Experience:

Bachelor’s degree in Analytics, Computer Science, Economics, Applied Mathematics, Statistics, Data Science, Operations Research, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Data Science (or closely related occupation) performing data analytics, building statistical models, and developing business intelligence applications to improve customer experience and drive business results in a financial services environment.

Or, alternatively, Master’s degree in Analytics, Computer Science, Economics, Applied Mathematics, Statistics, Data Science, Operations Research, or a closely related field (or foreign education equivalent) and four (4) years of experience as a Director, Data Science (or closely related occupation) performing data analytics, building statistical models, and developing business intelligence applications to improve customer experience and drive business results in a financial services environment.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) performing large-scale data extraction, transformation, and loading (ETL) processes in large data warehouses with SQL, Apache Hive, or Python; and integrating and managing data across databases and platforms (SQL Server, Oracle, or AWS S3).

• DE designing and building ML models (regression, classification, decision trees, clustering, and recommender systems) and Deep Learning (DL) models in Python, using Scikit-Learn, Transformers, or PyTorch; and performing distributed model training and hyperparameter optimization, using Amazon Web Services (AWS) SageMaker.

• DE validating and assessing model soundness and performance by conducting in-sample and out-of-sample testing, using Root Mean Squared Error (RMSE), R-squared, AUC ROC, Precision, or Recall; and documenting model assumptions, methodologies, limitations, and usage guideline to ensure adherence to model governance and model risk management policies.

• DE designing and implementing NLP solutions to enhance the efficiency of financial document processing and automation, using LLMs or generative AI technologies.

Salary: $190,000.00 - $212,000.00/year.

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