דרושים Applied Artificial Intelligence Machine Learning Sr Assoc ב-גיי פי מורגן ב-United States, New York

Job Responsibilities:

• Develop data model standards for capturing Conceptual, Logical, and Physical models to align with business objectives
• Work closely with Domain/Tower Information Architects, business stakeholders, and application teams to ensure data model standards are met
• Act as a representative for the organization at Firm-wide and Line of Business Information Architecture forums
• Offer technical leadership and guidance to ensure compliance with Information Architecture standards
• Develop and promote best practices in metadata management, data lineage, and data quality controls
• Perform regular assessments and audits of information architecture to maintain compliance and optimize processes
• Mentor and support team of architects in skill and expertise development

Required Qualifications, Capabilities, and Skills:

• 10+ years applied experience and formal training or certification on software engineering concepts with 5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise and more broadly across the organization
• Proven experience as an Information Architect or in a similar capacity and data architecture tools
• Strong proficiency in data modelling, metadata management, and information governance
• Proficiency in planning and managing workload, deliverables, and teams under tight deadlines
• Excellent communication and collaboration skills, with the ability to influence stakeholders at all levels
• Familiarity with regulatory requirements and data management standards
• Strong problem-solving skills and attention to detail
• Ability to abstract from specifics and detail from conceptual frameworks. Understanding of governing architectures, solutions, and teams
• Experience working on large-scale, global technology initiatives
• Knowledge of setting, using, and enforcing standards, industry patterns, and best practices

Preferred Qualifications, Capabilities, and Skills:

• Recent hands-on experience with Data Mesh Technologies such as Databricks
• Expertise in analyzing, modeling, depicting, and describing data architectures for diverse audiences

As a Head of Supplier Controls Intelligence, with in Global Supplier Service, you will play a crucial leadership role within the Corporate Third-Party Oversight (CTPO) organization, directly reporting to the Global Head of CTPO. Your role is designed to transform the Supplier Due Diligence teams by integrating state-of-the-art supplier controls methodologies. Your key responsibilities include optimizing intelligence collection processes, expanding visibility into supplier risks, and translating data into actionable insights. You will also be required to engage with senior executives, effectively communicate with stakeholders, explore innovative applications of intelligence across Third-Party Oversight (TPO) processes, and align initiatives with Lines of Business (LOBs). Furthermore, your position involves overseeing data analysis, fostering a culture of innovation, and building strong stakeholder relationships to propel control initiatives forward.

Job Responsibilities:

• Lead the adoption of cutting-edge methods for supplier controls to enhance data collection and improve risk visibility, contributing to an organization that values innovation, promoting a proactive approach to risk management.
• Streamline collection processes to maximize efficiency and effectiveness, ensuring timely and accurate data acquisition.
• Convert diverse data sets into cohesive, actionable insights, and enhance communication with stakeholders.
• Innovate the application of insights within Third-Party Oversight (TPO) processes, providing assessors with indirect information and summarizing findings into thematic risk categories.
• Work closely with Lines of Business (LOBs) to ensure efforts are aligned with business objectives and risk management strategies.
• Develop and implement strategies to capitalize on advancements in supplier controls, enhancing risk management capabilities.
• Drive the transformation of SAS into an organization focused on management of residual risk.
• Oversee the collection, analysis, and dissemination of data to supportdecision-making andrisk mitigation.
• Engage with senior regulators to inform and influence best practices in risk management, ensuring compliance and proactive risk mitigation.
• Foster a team culture that prioritizes innovation and continuous improvement, encouraging creative solutions to complex challenges.
• Build and maintain strong relationships with internal and external stakeholders to support and advance strategic initiatives.

Required qualifications, capabilities, and skills

• 15+ years experience in a senior leadership role specializing in third-party risk management, demonstrating a strong track record of success.
• In-depth expertise in supplier controls intelligence and risk management practices, with a focus on implementing industry best practices.
• Demonstrated proficiency in integrating and interpreting complex data from diverse sources to drive informed decision-making.
• Outstanding communication and collaboration skills, with the ability to work seamlessly across cross-functional teams and foster a cooperative work environment.
• Proven capability to effectively engage and build relationships with senior regulators, influencing risk management practices and ensuring compliance.
• Strategic thinker with a history of successfully driving organizational transformation and fostering innovation, leading to enhanced performance and growth.

As a Fraud Risk Senior Product Delivery Associate within our strategic fraud risk initiatives team, you will be instrumental in shaping the technology solutions that promote our operations. Positioned at the crossroads of business and technology, you will collaborate with colleagues across various business lines to understand challenges and opportunities. This knowledge will be transformed into high-quality technical requirements. Furthermore, you will coordinate with technical delivery teams to ensure that the solutions not only meet all requirements but also provide an exceptional business and customer experience.

Job responsibilities

• Partner with Fraud Risk product owners, data scientists, and fraud strategists on various initiatives to facilitate and drive customer focused solutions across the organization, serving as a subject matter expert to major business processes and supporting applications/capabilities
• Manage the interdependencies between product releases and other product delivery teams and activities required for end to end delivery
• Design solutions and improve existing software systems and applications to meet business requirements, working with stakeholders and technology partners
• Conduct and lead technical and functional JAD sessions, driving the team during solution design and defining web services API contracts. build requirement artifacts, data flow diagrams, user stories, use cases, mapping documents, and defining test scenarios.
• Elicit accurate functional and technical requirements and user stories with supporting acceptance criteria.

Required qualifications, capabilities and skills:

• Bachelor’s degree, in engineering, computer science, technology, or related field.
• 5+ years of experience in financial / banking services.
• Demonstrated ability to interpret and share concepts clearly & unambiguously. Being able to discuss topics with across varied audiences of business & technical resources. Comfortable creating and presenting recommendations to leadership.
• Innate listening skills with ability to interview stakeholders, quickly understand new concepts and ask appropriate probing questions to build full picture
• Self-starter & able to manage projects from ideation through completion with strong problem-solving skills and ability to deliver actionable insights
• Ability to handle multiple projects while managing conflicting deadlines and handling ambiguity. Regularly assessing your own performance and adapting your work to achieve better results.
• Experience with service-oriented design and technology (Rest APIs, micro services, Kafka, webservices, MQ messaging)
• Sound knowledge and proficiency with project tracking and process documentation tools like Confluence, JIRA, and Visio

Preferred qualifications, capabilities and skills:

• An advanced degree is a plus.
• Experience with fraud risk and originations products is a plus

Job responsibilities

• Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks
• Be accountable for decisions that influence teams’ resources, budget, tactical operations, and the execution and implementation of processes and procedures
• Ensures successful collaboration across teams and stakeholders
• Identifies and mitigates issues to execute a book of work while escalating issues as necessary
• Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team
• Creates a culture of diversity, opportunity, inclusion, and respect for team members and prioritizes diverse representation

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertise

• Practical cloud native experience and Certified in Public cloud with AWS required.
• System Design, Design Patterns, Architecture, Strong Hands-on, Java, Microservices, Kafka, AWS techstack like EKS, EMR, EC2, S3 Buckets, Networking, infrastructure, Database (Postgres, Dynatrace), FinOps, Resiliency, Observability, POC, Prototyping and experimentation with latest and greatest market tech stack
• Experience leading teams of technologists
• Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives
• Experience with hiring, developing, and recognizing talent
• In-depth knowledge of the services industry and their IT systems
• Practical cloud native experience
• Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines

Preferred qualifications, capabilities, and skills

• Preferably AWS Solutions Architect – Associate or Professional
• Soft Skills Like presenting, Negotiating, Mentorship, stakeholder management

Job responsibilities

• Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
• Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
• Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
  

Required qualifications, capabilities, and skills

• PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 3 years of industry or research experience in the field.
• Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods
• Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
• Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
• Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
• Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
• Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities, and skills

• Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development
• Knowledge in search/ranking, Reinforcement Learning or Meta Learning
• Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code
• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal

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.
• 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.
• Hands on experience of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
• In-depth experience with /Ranking, Recommender systems, RAG (Similarity Search), Agent systems, and other advanced methodologies.
• 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.
• Leverage Spark for big data processing and analytics, optimizing data workflows and enhancing performance in distributed computing environments

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.