Position Description:

Designs and implements Machine Learning (ML) and Deep Learning (DL) algorithm approaches in multiple projects. Programs Machine Learning frameworks using Python and R. Develops and models software solutions using Natural Language Processing (NLP), Information Retrieval, Machine Comprehension, Question Answering/Conversational Artificial Intelligence (AI), Reinforcement Learning, Knowledge Graph, Causal Inference, and Design of Experiment. Conducts exploratory data analysis according to measurements, unstructured data analysis, predictive analytics, and prescriptive analytics using Big Data, NLP, and chatbot technologies (Elasticsearch and Solr). Encourages ML and DL using TensorFlow, Keras, MXNET, and H2O.

Primary Responsibilities:

• Sets a strategic direction for data identification, collection, and qualification activities.

• Leads data analysis for multiple projects with diverse scope and complex business and technical challenges across several business units and functions.

• Coordinates and guides data science and data engineering elements of AI projects and ML techniques.

• Implements new technologies in a production environment with product, IT, and data engineering teams.

• Presents reports and findings to senior level technical and non-technical audiences.

• Develops and applies mathematical or statistical theory and methods.

• Collects, organizes, interprets, and summarizes numerical data to provide usable information.

Education and Experience:

Bachelor’s degree (or foreign education equivalent) in Computer Science, Data Science, Analytics, Operations Research, Engineering, Information Technology, Information Systems, Statistics, Mathematical Finance, or a closely related field and five (5) years of experience as a Senior Manager, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.

Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Data Science, Analytics, Operations Research, Engineering, Information Technology, Information Systems, Statistics, Mathematical Finance, or a closely related field and three (3) years of experience as a Senior Manager, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.

Or, alternatively, PhD degree (or foreign education equivalent) in Computer Science, Data Science, Analytics, Operations Research, Engineering, Information Technology, Information Systems, Statistics, Mathematical Finance, or a closely related field and no experience.

Skills and Knowledge:

Candidate must also possess:

• Demonstrated Expertise (“DE”) performing advanced statistical analytics to develop and evaluate supervised and unsupervised ML algorithms — Regression, Decision Trees, Neural Networks, Feature Selection, Hyper-Parameter tuning, and ranking models — using Python and ML libraries (scikit-learn, Tensorflow, Keras, or PyTorch).

• DE designing and developing NLP solutions to process unstructured and semi-structured text for NLP tasks – question answering, intent detection, classification, or clustering — using classical NLP and ML methods (Deep Learning (DL) and embeddings).

• DE launching ML and DL models in a production environment and performing data and runtime profiling of the solutions to assess the efficacy of the ML and AI algorithms.

• DE conducting ML research with financial applications, including portfolio construction, risk management, and factor investment.

[Expertise may be gained during Doctoral Program.]

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