Design, develop, and deploy AI/ML models using state of the art techniques available in the open stack (Python/PySpark/PyTorch) and/or vendor solutions
Partner with LOB leads to frame the problem, explore various ML/DL model architectures and methodologies, generate required artifacts related to model development life cycle (MDLC), author the model development document, and deliver AI models that meet business needs
Adhere to corporate model risk policy and ensure compliance with model risk management
Working with other data science teams to identify, gather, retain, and publicize modeling artifacts required for approved and repeatable processes
Work with AI technology and production teams to operationalize models
Work effectively in an agile project management methodologies for data science
Knowledge sharing with members of the team and across the organization on topics including machine learning algorithms, hyper-parameter tuning/search, and traversing across multiple big data platforms
Contribute to the CoE data science team’s group effort to stay current with the cutting edge NLP/ML/DL algorithms, methodologies in the open source community and vendor solutions.
4+ years of experience in an advanced scientific or mathematical field
A master’s degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science
4+ years of statistical modeling experience
3+ years of Python experience
2 + years of experience using quantitative machine learning techniques
2+ years of Hadoop experience
1+ years of Natural Language Processing (NLP) experience
Other Desired Qualifications
Hands on familiarity with machine learning and statistical modeling techniques applying machine learning techniques such as neural networks, random forest, GBM and SVM, Probabilistic Graphical Models, Deep Learning architectures, using open-source languages like Python, PySpark and/or PyTorch.
Experience with model monitoring and performance tracking
Hands on experience with deep learning toolkits such as Tensorflow, Keras, PyTorch, Dynet
Hands on experience writing data processing and data pipeline for model development including gathering and building datasets to collect intents, joining and aggregating source datasets, cleaning messy data, designing feedback loop on data needs
Experience building intent recognition and classification models. Experience with phrase level identification. Experience with language models such as BERT, ELMO, CRF
Experience with active learning and reinforcement learning
Experience with AI model transparency and explainability studies
Strong acumen in diagnosing and resolving data issues
Exceptional analytical, critical thinking, quantitative reasoning skills, and problem-solving skills.
Lead and/or support development of hierarchical categorization taxonomies using NLP unsupervised/supervised methodologies including enrichment of unstructured data to derive themes and trends, with specific focus on early identification of emerging themes.
Develop non-model and model development to generate actionable insights and uncover patterns (structured or unstructured) from multiple sources, while working in partnership with teams across Conduct Management.
Perform text analysis and advanced analytics including using Natural Language Processing, Machine Learning techniques and programming languages to derive relevant analysis and metrics, including building proof of concepts to determine value of implementing in future projects.
Collaborate with team to develop data driven analytics capabilities to identify anomalies, outliers, emerging trends and conduct risks across the Enterprise. Primary areas of focus include Internal Fraud, Sales Practice, Ethics, and allegations
Collaborate with team to design complex projects/analyses generally spanning multiple products/business lines/functional areas/data sources including analytical application of industry-leading experimental techniques or exploratory data analytics to support teams across Conduct Management.
Partner with other Conduct Management and LOB stakeholders to develop, and enhance analytical capabilities related to Conduct Management’s first line of defense
Offer strategic recommendations to senior stakeholders and leadership based on thought-provoking and sound analytics including communicating technical and business details to ensure understanding.
6+ years of experience in one or a combination of the following: reporting, analytics, or modeling; or a Masters degree or higher in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis and 4+ years of experience in one or a combination of the following: reporting, analytics, or modeling
2+ years of Python experience
2+ years of Natural Language Processing (NLP) experience
2+ years of statistical modeling experience
Extensive knowledge and understanding of research and analysis
Strong analytical skills with high attention to detail and accuracy
Excellent verbal, written, and interpersonal communication skills
Experience with design, implementation and governance with Artificial Intelligence, Natural Language Processing or Machine Learning Architecture
Knowledge and understanding of analytical methods used in: statistics or predictive modeling methods (regression modeling, clustering, pattern recognition, graphics)
2+ years of Tableau experience
Other Desired Qualifications
Model governance experience including writing model development documentation
Developing models to identify/detect emerging themes