Data Scientist [Multiple Positions Available]

JPMorganChase•Jersey City, NJ

7h•Onsite

About The Position

We are seeking a Data Scientist to build and train production-grade machine learning models on large-scale datasets to solve business use cases. This role involves using large-scale data processing frameworks to manipulate data, solving business use cases with Deep Learning models (NLP, LLMs), performing data modeling experiments, and ensuring high data quality. The ideal candidate will identify opportunities to adopt new methodologies and stay current with industry trends.

Requirements

Bachelor's degree in Mathematics, Computer Science, Data science or related field of study plus seven (7) years of experience in the job offered or as Data Scientist, Financial Reporting Analyst, or related occupation.
OR Master's degree in Mathematics, Computer Science, Data science or related field of study plus five (5) years of experience in the job offered or as Data Scientist, Financial Reporting Analyst, or related occupation.
Three (3) years of experience with developing and deploying machine learning techniques in financial domains, including regression, classification, clustering, and time series analysis.
Three (3) years of experience with designing and implementing financial engineering models to optimize stock borrow and loan strategies.
Three (3) years of experience with developing and refining Natural Language Processing models to extract insights from unstructured text data.
Three (3) years of experience with designing and tuning language models using deep neural networks to solve problems in areas including sequence prediction and language modeling.
Three (3) years of experience with implementing transformer-based models, including BERT, GPT and Focal loss function.
Three (3) years of experience with conducting Monte Carlo simulations for modeling and evaluating the impact of uncertainty and variability in firm's liquidity forecasts.
Three (3) years of experience with performing matrix computations and applying linear algebra techniques to optimize algorithms and improve the efficiency of machine learning models.
Three (3) years of experience with utilizing Spark, Hadoop, Shell Scripting, Pentaho and Qliksense Server Side Extensions to create Qlik plugins.
Three (3) years of experience with Kubernetes and Spark on Kubernetes.
Three (3) years of experience with machine learning (ML) model deployment using Jenkins pipeline.

Responsibilities

Build and train production grade machine learning models on large-scale datasets to solve business use cases.
Use large-scale data processing frameworks to manipulate and extract value from both structured and un-structured data.
Solve various business use cases involving forecasting and anomaly detection using Deep Learning models like Natural language Processing and Large Language Models.
Perform data modeling experiments, evaluating against strong baselines, and extracting key statistical insights and/or cause and effect relations.
Create data models using best practices to ensure high data quality and reduced redundancy.
Identify opportunities to adopt to the latest methodologies into existing implementations and stay current on industry trends.