818 Associate Data Governance jobs in New York,NY

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Client Service Specialist

Spectrum - New York, NY

Client Service Specialist

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Senior Associate, SailPoint Identity Governance Engineer

KPMG

New York, NY 10025

Onsite

Minimum three years of recent hands-on experience with IGA solutions, with at least one year specifically focused on SailPoint Identity Security Cloud (ISC)
Bachelor's degree from an accredited college or university
Application onboarding and migration experience; demonstrated experience contributing to at least one migration project from a legacy IAM solution (for example: Oracle Identity Manager, SailPoint Identity (IIQ)) to SailPoint ISC
Solid understanding of core Identity and Access Management principles, including identity lifecycle management, access requests, access certification, and role engineering; understanding of IAM and governance concepts, security controls, and regulatory requirements related to access governance (for example: SOX, NIST, ISO 27001); familiarity with cloud environments (AWS, Azure, or GCP)
Ability to travel as required
Applicants 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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Head of AI Data Science, Intelligence Ventures

Spectrum

New York, NY 10036

Onsite

Deep expertise in transformer-based sequence modeling and its application to behavioral or interaction data at consumer scale — including architecture design, training methodology, fine-tuning, and embedding quality evaluation
Proven track record developing and deploying household- or user-level embedding models applied to real-world use cases in media, marketing, commerce, and/or customer intelligence — not just research environments. Demonstrated understanding of the unique characteristics of behavioral sequence data: sparsity, temporal dynamics, multi-entity structure, and the signal differences between behavioral intent and explicit interaction
Strong command of the full data science lifecycle in production settings — from exploratory data analysis and feature engineering through model training, validation, deployment, monitoring, and iteration — at large dataset scale (billions, even trillions of records)
Hands-on proficiency with Python, PyTorch or TensorFlow, and distributed ML training frameworks; experience running ML workloads on cloud platforms (AWS SageMaker, Snowflake Cortex, Databricks, or equivalent)
Experience designing and operationalizing feature stores and predictive modeling pipelines that serve downstream intelligence products, audiences, or decision systems in production environments
Ability to communicate complex AI/ML concepts clearly to non-technical executive audiences, product stakeholders, and external partners; comfort operating as an external-facing technical spokesperson for the platform's modeling capabilities and intelligence differentiation
Track record of leading and growing high-performing data science teams; experience recruiting and developing senior ML talent in competitive markets
Genuine intellectual curiosity about the application of AI to behavioral science, consumer intelligence, and agentic systems; awareness of the evolving landscape of foundation models, retrieval-augmented generation, and multi-agent AI architectures
Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative field
Experience leading applied ML or data science teams building consumer-facing or enterprise intelligence products — 7 years
Hands-on experience designing and training transformer or deep learning models on sequential behavioral data at scale — 5 years
In-office position preferably based in New York City
Travel as required for partner engagements, executive meetings, and industry events

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Associate, Internal Product Specialists

Goldman Sachs & Co. LLC

New York, NY 10060

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Manager, SailPoint Identity Governance Technical Lead

KPMG

New York, NY 10025

OnsiteHealth InsuranceRetirement Benefit

Minimum five years of recenthands-on experience with IGA solutions, with at least two years specificallyfocused on SailPoint Identity Security Cloud (ISC)
Bachelor's degree from anaccredited college/university in computer science, information security, or arelated field is required
SailPoint professional certifications (for example:SailPoint Certified IdentityNow Engineer) are preferred
Provenapplication onboarding and migration expertise, including leading at least onesignificant migration from legacy IAM solutions (e.g., Oracle Identity Manager,SailPoint IIQ) to SailPoint Identity Security Cloud (ISC)
Deepunderstanding of IAM and access governance (identity lifecycle, accessrequests, certification, role engineering), security controls, and regulatoryframeworks (e.g., SOX, NIST, ISO 27001); familiarity with AWS, Azure, and GCP
Abilityto lead technical workstreams, make informed decisions, mentor team members,and drive complex identity governance initiatives
Excellentanalytical, communication, presentation, and problem-solving skills, with theability to lead technical discussions; knowledge of AI tools and integrations,including management of non-human and agent identities
Ability to travel as required
Applicants 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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Senior Technologist, Data Center Fluids

Wayne, NJ 07470

HybridFlexible ScheduleHealth InsuranceRetirement Benefit

Degree in Chemistry, Engineering, or related technical discipline.
Up to 25% travel should be expected with this role
This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.

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Human Resources Technology Data Engineer

LHH US

New York, NY 10025

$85-$100/hr

HybridHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field.
5-8 years of professional software engineering experience.
Proven track record of hands on development in enterprise scale systems, preferably in HR.
Strong proficiency in at least one core programming language (Python or Java).
Deep experience with relational databases, NoSQL stores, and complex query design.
Experience working with HR, people operations, or workforce analytics data, including sensitive data handling, HRIS integrations (e.g., Dayforce, Culture Amp, etc.), and secure data exchange patterns.
Demonstrated ability to build or support platforms involving employee lifecycle data, compensation structures, organizational hierarchies, and talent management workflows.

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Client Executive - NYC Dept. of Education

NTT DATA Services, LLC

New York, NY 10261

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Human Resources Technology Data Engineer

LHH US

New York, NY 10022

$85-$100/hr

HybridHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field.
5-8 years of professional software engineering experience.
Proven track record of hands on development in enterprise scale systems, preferably in HR.
Strong proficiency in at least one core programming language (Python or Java).
Deep experience with relational databases, NoSQL stores, and complex query design.
Experience working with HR, people operations, or workforce analytics data, including sensitive data handling, HRIS integrations (e.g., Dayforce, Culture Amp, etc.), and secure data exchange patterns.
Demonstrated ability to build or support platforms involving employee lifecycle data, compensation structures, organizational hierarchies, and talent management workflows.

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New, Posted 14 hours ago

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Senior Associate, Trade Processing

Goldman Sachs & Co. LLC

New York, NY 10060

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New, Posted 21 hours ago

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Principal Engineer - Python API Development

Fidelity Investments

Jersey City, NJ 07311

~ 22 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.