Machine Learning Scientist jobs at Jpmorgan in United States, Jersey City

As a Data Scientist Vice President within the Compliance, Conduct Operational Risk (CCOR) Data Analytics team, you will be responsible for devising and developing Proofs of Concept (POCs) and deployable models using AI/Gen AI/ ML techniques, algorithms and other statistical and numerical methods. You will need to be able to extract and work with large volumes of data (both structured and unstructured) from multiple sources, transforming it into an analysis-ready format to develop the data pipeline. Additionally, you are expected to independently formulate methodologies, and quantitative and analytical tasks, from business problems.

Job 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

Required qualifications, capabilities, and skills

• 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 qualifications, capabilities, and skills

• 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

Job responsibilities

• Executes research and experimentation with Large Language Models and other Generative AI technologies to solve complex risk technology challenges
• Produces scalable and production-ready AI systems that integrate with existing risk calculation frameworks
• Gathers, analyzes, and synthesizes insights from diverse data sets to improve AI model performance and risk assessment capabilities
• Writes secure and high-quality code using Python and relevant AI/ML frameworks
• Designs and implements AI solutions that enhance operational efficiencies across business and technology functions
• Design and develop fast, responsive and visually appealing user interfaces using React, HTML, and CSS, ensuring a seamless user experience.
• Implement and maintain reusable code and libraries for future use, ensuring consistency and efficiency in UI as well as backend development.
• Mentors junior team members in AI/ML technologies and approaches
• Participate in code reviews and provide constructive feedback to peers, fostering a culture of continuous improvement and learning.
• Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on AI/ML applications, software engineering concepts and proficient applied experience
• Hands-on experience with Large Language Models (GPT, BERT, etc.)
• Strong understanding of Generative AI concepts and applications
• Proficiency in prompt engineering techniques
• Advanced Python programming skills
• Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face)
• Familiarity with cloud-based AI services (AWS, Azure, or GCP)
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages.
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Overall knowledge of the Software Development Life Cycle, with a focus on both front-end and back-end development processes and best practices.
• Strong communication skills to explain complex technical concepts

Preferred qualifications, capabilities, and skills

• Experience working in financial domain is a plus.
• Knowledge of model fine-tuning and Retrieval Augmented Generation (RAG)
• Experience with AWS/Databricks/Kubernetes/AI & ML.
• Experience with large-scale database technologies
• Previous experience applying AI solutions to business problems

As a Senior Internal Audit Associate within the Chief Data & Analytics organization, you will assist with ongoing risk assessment, control identification, audit execution, and continuous monitoring activities. This role is perfectly suited for an experienced IT audit professional with a keen interest and understanding of Artificial Intelligence and Data, as well as the audit and risk skills necessary to effectively execute global audits.

Job Responsibilities:

• Participate in audit engagements from planning to reporting and produce quality deliverables to both department and professional standards while ensuring audits are completed timely and within budget
• Partner with colleagues and stakeholders to evaluate, test and report on the design and operating effectiveness of management’s controls
• Communicate audit findings to management and identify opportunities for improvement
• Create and maintain collaborative working relationships with stakeholders, while providing independent challenge
• Contribute to a collaborative working environment with team members and peers, supporting a culture that encourages integrity, respect, excellence and innovation
• Stay up to date with evolving industry and regulatory developments
• Find ways to drive efficiencies in audit process through automation while embracing the innovative opportunities offered by new technologies

Required qualifications, capabilities and skills:

• Bachelor's degree (or relevant financial services experience) required.
• Experience with auditing technology controls and an understanding of emerging technology (e.g., Artificial Intelligence/Machine Learning).
• One of the following professional qualifications is required: Certified Information Systems Auditor (CISA), Certified Information Systems Security Professional (CISSP).
• Experience with internal audit methodology and applying concepts in audit delivery and execution.
• Solid understanding of internal control concepts, with the ability to evaluate and determine the adequacy of controls by considering business and technology risks in an integrated manner.
• Excellent verbal and written communications skills.
• Advanced analytical skills, particularly in regard to assessing the probability and impact of an internal control weakness.
• Enthusiastic and self-motivated, with a keen interest in learning; effective under pressure and willing to take personal responsibility/accountability.

DESCRIPTION:

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Engineering (any), Computer Science, Data Science, Statistics, Data Analytics, Applied Mathematics or related field of study plus 3 years of experience in the job offered or as Data Scientist - Applied AI and ML, Data Scientist, Data Scientist (Lifecycle Analytics), Business Analytics 3 (Marketing Analytics), Consulting Analyst, or related occupation.

Skills Required: This position requires experience with the following: working on data science projects in marketing, operations, and pricing domains; supervised and unsupervised machine learning algorithms including boosting trees and clustering techniques using R; modeling with XGBoost, Random Forest, and clustering; applied statistical and mathematical techniques including A/B testing, correlation analysis, gradient descent optimization, and operations research models; data wrangling tools including SQL Teradata and Hadoop, Alteryx, and IBM Cognos Analytics; Alteryx for data mining, data wrangling, and aggregation; preparing detailed AI and ML model documentation; model evaluation techniques including AUC and Gain Chart; SHAP to interpret and explain predictions of complex machine learning models.

Job Location: 480 Washington Blvd, Jersey City, NJ 07310.

Full-Time. Salary: $195,100 - $260,000 per year.

As a Machine Learning Engineer within our platform operations team, you will be tasked with the design, construction, and maintenance of our AIOps solution. This role demands a profound knowledge of AI/ML technologies, IT infrastructure, and platform engineering.

Job Responsibilities:

• Design, develop, and maintain software applications with integrated AI/ML capabilities with a key focus on AIOps.
• Collaborate with cross-functional teams to gather and analyze requirements, translating them into technical solutions.
• Develop and implement software architecture and design patterns to ensure scalability and performance.
• Write clean, maintainable, and efficient code in one or more general-purpose programming languages: Python, Java, C, C++, Go.
• Implement and manage data pipelines to preprocess and transform data for AI/ML models.
• Integrate AI/ML models into software applications and ensure seamless deployment into production environments.
• Optimize software applications for performance, reliability, and scalability.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay up-to-date with the latest advancements in software engineering and AI/ML technologies.
• Ensure adherence to software development best practices, including agile and lean methodologies.
• Apply SRE principles to enhance system reliability, performance, and availability. Implement monitoring and alerting solutions to proactively identify and resolve issues.

Required Qualifications, Capabilities, and Skills:

• Bachelor’s degree in Computer Science or equivalent practical experience.
• Strong experience working with multiple technology teams in a matrixed organization.
• 7+ years of experience as a software developer with a focus on integrating AI/ML solutions.
• Strong programming skills in Python, with experience in developing and maintaining production-level code.
• Experience with application architecture and design patterns.
• Proficiency in working with large datasets and data preprocessing.
• Solid understanding of AI/ML algorithms and techniques, including deep learning and natural language processing.
• Familiarity with AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, and Keras.
• Experience with cloud platforms, such as AWS or Azure, for deploying and scaling software applications.
• Strong problem-solving and analytical skills and excellent communication and collaboration skills.

Preferred Qualifications, Capabilities, and Skills:

• Familiarity with DevOps practices for software deployment and monitoring.
• Experience with SQL and NoSQL databases, Linux/Unix environments, and tools like Terraform and Apache Kafka.
• Experience with distributed computing frameworks, such as Apache Spark.
• Experience in implementing SRE practices to improve system reliability and performance.