1027 Application Development Analyst Oracle jobs in New York,NY

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Principal Quant Developer (MLOps)

Fidelity Investments

North Bergen, NJ 07047

~ 18 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field
Six (6) years of experience as a Senior Quant Developer or similar role
Alternatively, a Master's degree (or equivalent foreign education) in the same fields
Four (4) years of experience as a Lead Quantitative Development or similar role
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
Expert in Python with experience across the development stack (full stack)
Exposure to object-oriented programming (OOP) and design patterns
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability
Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
Proven ability to construct and manage robust data pipelines and event-driven workflows
Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2
Experience in containerization with Docker and orchestration with Kubernetes
Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
Awareness of responsible AI governance practices
Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset
Demonstrated knowledge of mathematics, statistics, and quantitative finance
Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
Domain knowledge in either equities, fixed income or alternative asset classes

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New, Posted 1 hour ago

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Lead Specialist, Oracle GL/AP

KPMG

New York, NY 10025

OnsiteHealth InsuranceRetirement Benefit

Minimum five years of recent experience supporting medium to large applications, working directly with internal/external clients
Bachelor's degree from an accredited college/university in an appropriate field
Experience with Oracle implementations, post-production support, upgrades and functional testing with understanding of Information Technology Infrastructure Library (ITIL) framework, Information Technology Service Management (ITSM) and service desk management; strong configuration skills across Oracle Cloud Applications.
Required module experience: Oracle General Ledger, Accounting Hub, Project Billing and Costing, Accounts Payable, Accounts Receivable and Lease Accounting
Capability to work independently and take ownership of and complete relatively complex tasks, effectively using available resources, as needed, with minimal guidance; ability to work well as part of a mixed team including, project managers and technical consultants, client personnel (both on and offshore)
Excellent written and verbal communication, facilitation, and presentation skills; strong attention to detail with a high level of accuracy and written and oral communications skills and the ability to articulate ideas effectively
Ability to travel as necessary depending on client and business needs
Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

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Principal Quant Developer (MLOps)

Fidelity Investments

Lyndhurst, NJ 07071

~ 23 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field
Six (6) years of experience as a Senior Quant Developer or similar role
Alternatively, a Master's degree (or equivalent foreign education) in the same fields
Four (4) years of experience as a Lead Quantitative Development or similar role
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
Expert in Python with experience across the development stack (full stack)
Exposure to object-oriented programming (OOP) and design patterns
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability
Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
Proven ability to construct and manage robust data pipelines and event-driven workflows
Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2
Experience in containerization with Docker and orchestration with Kubernetes
Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
Awareness of responsible AI governance practices
Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset
Demonstrated knowledge of mathematics, statistics, and quantitative finance
Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
Domain knowledge in either equities, fixed income or alternative asset classes

SmartExplore AI is experimental.

New, Posted 1 hour ago

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Manager, Oracle Fusion Manufacturing & Quality

KPMG

New York, NY 10025

A minimum of Five years of management consulting experience with a focus on Oracle Fusion Supply Chain work, Manufacturing & Quality
Bachelor's degree in an appropriate field from an accredited college/university
Completion of at least one implementation in Oracle Fusion Manufacturing & Quality is preferred
Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)
Travel may be up to 80-100%

SmartExplore AI is experimental.

New, Posted 8 hours ago

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IT Risk Operations - Sr Analyst

Northwestern Mutual

New York, NY 10025

Flexible Schedule

New, Posted 2 hours ago

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CIB Finance Analyst, ACPM

Santander Holdings USA

New York, NY 10022

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Business Development Manager, STEM Partnerships

Liberty Science Center

Jersey City, NJ 07305

~ 22 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

Valid driver's license (required)
Minimum 3 years of experience in educational sales, with a focus on expanding and developing a client portfolio
At least 3 years of experience in customer service and relationship management
Bachelor's degree in business, marketing, or a STEM-related field (preferred but may be considered part of qualifications; included as stated in preferred qualifications but not to be moved here)
Ability to work at least eight hours per day, Monday through Friday, with flexibility for evenings and weekends as needed
Travel to partner sites and conferences will be required
Travel to conferences, meetings, and partner sites to observe off-site programming will be required. Ability to drive is a requirement
Physical ability to carry up to 25 lbs of equipment or supplies and to stand/walk/move for extended periods
On-site work in open floor plan environments; ability to work in such environments

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Head of Technology, Intelligence Ventures

Spectrum

New York, NY 10036

Onsite

Deep expertise across the full intelligence platform stack — including distributed data pipelines, ML platform architecture, embedding systems, feature stores, agent-to-agent API design, and LLM-powered application layers — with demonstrated ability to architect and ship all layers as a coherent, production-grade product
Demonstrated experience architecting and operating consumer data intelligence or data product platforms underpinned by complex machine learning systems and built on modern, cloud-native data infrastructure
Hands-on proficiency with Snowflake (including Cortex, Native Apps, and data sharing frameworks), cloud data platforms (AWS, Azure, or GCP), and production ML/AI systems at scale
Experience building agentic AI systems and LLM-powered product interfaces — including agent-to-agent APIs, retrieval-augmented generation architectures, and natural language UIs grounded in proprietary data — with strong product instincts around accuracy, trust, and user experience for non-technical enterprise audiences
Proven ability to translate complex technical architecture into clear executive and partner-facing communications; comfortable engaging at the C-suite level and in strategic partner negotiations with hyperscalers and technology platforms
Strong understanding of privacy-preserving data architecture, including differential privacy, de-identification techniques, zero-copy and clean room frameworks, and the regulatory landscape governing consumer behavioral data
Track record of recruiting and developing exceptional engineering talent in competitive markets; experience building high-performance teams from early-stage through scaled operations
Experience managing external development partners and outsourced engineering resources alongside an internal team in a fast-moving, build-from-scratch environment
Ability to operate in an ambiguous, early-stage environment while maintaining rigorous engineering standards and delivering against aggressive milestones
Experience building externally-consumed data or intelligence platforms — including developer-facing APIs, data marketplace integrations, or partner-accessible data products — with strong instincts around developer experience, access governance, and commercial platform design
Bachelor's Degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field
Experience leading consumer data intelligence, AI/ML platform, or data product engineering organizations — 10 years
Engineering leadership and team-building experience, including managing senior technical staff — 7 years

SmartExplore AI is experimental.

New, Posted 1 day ago

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