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Chase · 4 weeks ago

Compliance - Data Scientist - Vice President

1230 Avenue Of The Americas, New York, NY, 10020, US

Full-time

Onsite

Mid, Senior Level

$147K/yr - $215K/yr

6+ years exp

Chase is a leading financial services firm, and they are seeking a Data Scientist Vice President within the Compliance, Conduct Operational Risk Data Analytics team. The role involves developing Proofs of Concept and deployable models using AI/Gen AI/ML techniques to address business challenges and ensure compliance with regulations.

BankingFinancial Services

Responsibilities

Analyze complex/unstructured data to understand the business problem and use case

Analyze business requirements, design, and develop appropriate methodology

Develop deployable, scalable and effective models/ analytical methods as part of technology managed system or as a self-served application of a business user

Work collaboratively and creatively with other data scientists, technology partners, risk professionals, model validation teams, etc

Prepare technical documentation of quantitative models for internal model risk and governance review

Qualification

PythonMachine LearningGraph AnalyticsData Pipeline DevelopmentDeep LearningStatistical ModelsGraph DatabaseQuery LanguageAgile SDLCCommunication Skills

Required

6+ years of related experience in Python, R or Scala with Bachelor of Science degree in Computer Science, Physical Sciences, Econometrics, Statistics, or other any quantitative discipline

Demonstrable theoretical and application knowledge of AL/ ML, Gen AI and Statistical Models

Demonstrable hands-on experience with Transformer or other deep learning architectures in real applications

Demonstrable hands-on experience with using or fine tuning multimodal LLM in real business applications with scale and performance

Demonstrable hands-on experience and familiarity with any or all of the following packages, algorithms, and/or alternatives, including Graph Learning Packages : (NetworkX, Torch-Geometric, Graphframes, Graphistry), ML Packages (Pandas, Scikit-Learn, XGBoost, catboost, lightgbm, automl, Optuna, Hyperopt), Visualization Packages (Matplotlib, Seaborn, Geopandas), Algorithm (Ensemble Louvian / Hierarchical Clustering, Label Propagation, Connected Component Analysis, Graph Neural net (Graph Attention Network), Page Rank, Centrality Analysis, Tree based Analysis, Outlier Detection Methods, Zero Shot/ Few Shot learning)

Demonstrable experience with graph analytics, graph-based learning, and graph representation/visualization

Experience in graph Database: TigerGraph, Neo4j

Experience in Query Language: Hive, Cypher (Graph Query Language)

Experience in developing and operationalization of data pipelines

Familiarity and experience of assimilating large amounts of data from multiple databases and utilize them for creating actionable outcome; Adhering to a standardized analysis and project methodology; and documenting quantitative analysis

Experience with processes, controls and governance of a highly regulated environment; Self-starter and strong influencing skills with strong communication skills

Preferred

Hands-on professional experience in software development especially with analytical & computationally intensive systems, digital transformations leveraging cloud technologies (AWS, GCP, Azure, Databricks etc.). Experience with EKS or AKS provisioning is a plus

Post graduate degrees such as Master's Degree, PhD, etc. is preferred

Real life exposure to Agile SDLC, ModelOps and /Or Design Thinking is desirable

Working knowledge of C/C#/C++ or others is a plus

Experience in financial services industry especially in Operational Risk Management, Anti-Money Laundering & Know Your Customer, Trade Surveillance model development