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Data Jobs in New York

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Today

Manager, Applied AI Engineer

Alvarez and Marsal New York, NY

New York, NY

Today

$140k - $180k/yr Full time Manager Agentic Ai Ai Agent

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Job Description

Alvarez and Marsal’s AI Lab team, part of the firm’s Global AI & Knowledge Organization (GAIKO), is focused on turning repeatable business workflows into trusted, governed AI that can scale across everyday consulting work. In this onsite role in New York, you will lead end-to-end delivery of applied AI solutions, bringing together business needs, production data, and agent design to create skills and agents that can operate reliably across the firm.

You will own delivery from proof of concept through deployment and ongoing iteration, partnering with business unit leaders, Knowledge Management and Data, and engineering teams to ensure success metrics are clear and AI workflows meet governance and responsible AI expectations.

Responsibilities

Own end-to-end delivery of applied AI solutions, covering problem framing, build, deployment, monitoring, and iterative improvement from proof of concept to production.
Partner with business unit leaders and their teams to understand how work happens today, translate needs into skills and agents, and align on clear success metrics.
Work with Knowledge Management and Data team leads to gather and clarify requirements, then translate them into skill and agent designs.
Partner with Data Engineering, BIU, and the Intelligence Layer teams to ensure solutions are built on reliable, production-grade data.
Design, build, and operate headless skills and agentic workflows, including multi-step orchestration, tool routing, retrieval, guardrails, evaluation, and human-in-the-loop controls.
Build and maintain automated skill-building pipelines, including templates, scaffolding, testing and evaluation harnesses, packaging, and deployment to enable fast, consistent releases.
Create integrations with large language model platforms and use the Model Context Protocol (MCP) to make skills available to approved AI tools and the Intelligence Layer.
Integrate structured and unstructured enterprise content while preserving source permissions, metadata, and governance requirements.
Guide the team in assessing current Power Platform and Microsoft stack processes, reimagining them as AI-first workflows rather than one-to-one rebuilds, and converting them into skills and agents or connecting them to them.
Train the broader team through workshops, playbooks, templates, worked examples, and office hours on how to build skills.
Mentor engineers via pairing, code and design reviews, and hands-on coaching to raise quality for skills and agents across the pod.
Help shape engineering standards for skills and agents with the Intelligence Layer tech lead, including evaluation, CI/CD, versioning, reproducibility, and performance monitoring.
Recommend tools, frameworks, and design patterns. Technical decisions are made by the Intelligence Layer tech lead together with the Intelligence Layer lead.
Support responsible AI use, including data privacy, client confidentiality, model risk, and decisions about third-party models.
Communicate results, tradeoffs, risks, and blockers clearly to pod leadership, the Intelligence Layer tech lead, business unit leaders, and senior stakeholders in business terms.

Requirements

Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
Cloud or AI-related certifications are a plus.
5+ years of software engineering, data science, machine learning, or applied AI engineering, including 2+ years building and shipping LLM or agent-based systems in production.
Strong hands-on Python development experience.
Experience building LLM and generative AI applications, including RAG, prompting, evaluation, and agentic patterns.
Proven track record designing, building, and shipping multiple AI agents and skills into production (examples or a portfolio discussed at interview).
Experience building automated pipelines for creating, testing, evaluating, and deploying skills or agents at scale.
Hands-on experience with MCP, agent frameworks (examples include Claude Agent SDK, LangGraph, Semantic Kernel, or similar), and reusable skill design.
Experience with CI/CD, testing, and observability for production systems.
Ability to explain technical concepts in plain business language and run discovery sessions with business unit leaders to draw out real requirements.
Proven mentoring and teaching experience, including upskilling engineers or non-technical colleagues.
Comfort presenting to and facilitating workshops with senior stakeholders.
Strong collaboration skills and ability to build relationships across teams.
Bias toward action, shipping often and iterating based on feedback.
High ownership and comfort with ambiguity and shifting priorities, with judgment on when to ship, iterate, or stop.

Technologies

Python
LLM
Agent-based systems
RAG
MCP (Model Context Protocol)
Claude Agent SDK
LangGraph
Semantic Kernel
Power Platform
SharePoint
Power BI
Power Automate
Power Apps
Azure
Fabric/Power BI
SQL
CI/CD

Benefits

Healthcare plans
Flexible spending and savings accounts
Life, AD&D, and disability coverages
401(k) retirement savings plan
Annual discretionary contribution to their 401(k) retirement savings plan from Alvarez & Marsal (if eligibility requirements are met)
Paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part time employees), and ten federal holidays
One floating holiday
Parental leave
Discretionary bonus program (based on a number of factors, including individual and firm performance)

Location: New York, NY (onsite). Salary range: USD 140,000 - 180,000 per year. Experience level: 5+ years.

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1d ago

Senior Data Engineer

Robotics Technologies New York, NY

New York, NY

1d ago

Full time Senior Data Engineer Data Engineering

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Job Description

Robotics Technologies is hiring a Senior Data Engineer onsite in New York, NY to build a modern, scalable healthcare enrollment data platform with a focus on X12 EDI processing.

Responsibilities

Design, develop, and maintain scalable data pipelines using Databricks.
Build and support X12 EDI processing capabilities, with emphasis on 837, 835, and 834 transactions.
Develop high-volume, production-grade data engineering solutions.
Work with Delta Lake, Apache Spark, Databricks Notebooks, and Databricks Pipelines.
Process and transform healthcare enrollment, eligibility, and claims-related data.
Ensure data security and compliance aligned with HIPAA guidelines, including proper handling of PII and PHI.
Troubleshoot, optimize, and maintain existing data pipelines.
Operate independently within a fast-paced program environment.

Requirements

6+ years of experience in Data Engineering.
Strong hands-on experience with Databricks including Delta Lake, Spark, Notebooks, and Pipelines.
Strong working knowledge of X12 EDI standards, specifically 837, 835, and 834.
Proficiency in Python and PySpark.
Experience building and maintaining high-volume, production-grade data pipelines.
Healthcare domain experience, including knowledge of PII, PHI, and HIPAA compliance.
Familiarity with healthcare enrollment and eligibility data workflows.
Ability to work independently and deliver in a fast-paced environment.

Technologies

Databricks
PySpark
Python
X12 EDI
Delta Lake
Apache Spark
Databricks Notebooks
Databricks Pipelines

Good to Have

Previous experience with healthcare clearinghouse integrations.
Experience with healthcare EDI transaction processing and integrations.

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2d ago

Senior Associate - Full-Stack AI Engineer

New York Life New York, NY

New York, NY

2d ago

$124k - $177k/yr Full time Senior Artificial Intelligence Azure

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Job Description

Hybrid (3 days per week) in New York, NY, this role supports the investment business by building and maintaining applications and data flows across Trading, Accounting, and Datawarehouse platforms. You will leverage Generative AI to improve productivity and streamline processes, while designing scalable software solutions and assessing new technologies through POCs and prototypes.

As a Senior Associate Full-Stack AI Engineer (Level PF4), you’ll work with product, architecture, engineering, and business partners to deliver enterprise-quality outcomes with a focus on reliability, maintainability, security, and user experience. You’ll also keep pace with advancements in LLMs, cloud platforms, and modern software engineering practices to identify opportunities for efficiency and automation.

What you’ll do

Design, develop, and build scalable, high-performance applications that align to business requirements and emphasize reliability, maintainability, security, and strong user experience.
Collaborate across teams (product, architecture, engineering, and business partners) to translate requirements into enterprise-quality software solutions.
Run proofs of concept (POCs) and build prototypes to evaluate new technologies, validate approaches, and address emerging business and technical needs.
Drive reuse and consistency by designing reusable components, frameworks, and modern capabilities that can be leveraged across applications and teams.
Stay current with Generative AI, LLMs, cloud, and software engineering practices to improve efficiency, automation, and business outcomes.
Explain complex technical concepts clearly to both technical and non-technical stakeholders and collaborate effectively with global and distributed teams, including offshore partners.
Maintain strong ownership and prioritization, working independently and collaboratively to deliver high-quality results in a fast-paced environment.
Support the investment business through building and maintaining applications and designing, developing, and maintaining data flows between Trading, Accounting, and Datawarehouse platforms.

What you bring

8–12 years of hands-on software development experience.
Solid understanding of the full Software Development Lifecycle (SDLC).
Proficiency with Agile and Waterfall methodologies.
Flexible mindset to work across different platforms and projects.
Strategic thinking with awareness of business needs and regulatory pressures.
Up-to-date knowledge of architecture trends and systems best practices.
Excellent written and verbal communication skills across all levels of the organization.
Working knowledge of GIT, Team Foundation Server (TFS), JIRA, and CI/CD pipelining.
Experience with Python, C#, .NET Core, Angular, and TypeScript.
AI/LLM engineering experience with AWS Bedrock, Claude, OpenAI, and MCP.
Cloud platform experience with AWS (or Azure/GCP).
Data engineering experience with Oracle, SQL Server, and PostgreSQL.
Enterprise integration and API development.
DevOps and CI/CD automation experience with Jenkins and Harness CI/CD.

Technologies you’ll work with

Python, C#, .NET Core, Angular, TypeScript
AWS Bedrock, Claude, OpenAI, MCP
AWS Services, Azure, GCP
Oracle, SQL Server, PostgreSQL
GIT, Team Foundation Server (TFS), JIRA
CI/CD Pipelining, Jenkins, Harness CI/CD

Benefits

Leave programs
Adoption assistance
Student loan repayment programs
Annual discretionary bonus eligible: Yes

Compensation and pay transparency

Salary range: $124,000 - $177,000 per year
Overtime eligible: Exempt
Sales bonus eligible: No
Actual base salary is determined based on factors including experience, skills, qualifications, and job location.
Employees may be eligible for an annual discretionary bonus.
In addition to base salary, employees may also be eligible to participate in an incentive program.

Job requisition ID: 95137

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2d ago

Senior Associate - Full-Stack AI Engineer

New York Life New York, NY

New York, NY

2d ago

$100k - $143k/yr Full time Backend Developer Senior Angular

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Job Description

New York Life is hiring a Senior Associate (investment technology) for the Tech Data AI Ventures team in New York, NY (hybrid). This role blends full-stack software engineering with applied Generative AI, helping the investment business build and maintain applications and design end-to-end data flows between Trading, Accounting, and datawarehouse platforms. You will also contribute reusable components and modern capabilities that can be leveraged across applications and teams.

Compensation: $100,000 to $143,000 per year. Overtime eligible: Exempt. Discretionary bonus eligible: Yes. Sales bonus eligible: No.

What you can expect

Full benefits package including leave programs, adoption assistance, and student loan repayment programs
Annual discretionary bonus
Hybrid work with 3 days per week in office

Responsibilities

Design, develop, and build scalable, high-performance applications aligned with business requirements, with focus on reliability, maintainability, security, and user experience
Conduct proofs of concept and develop prototypes to evaluate new technologies, validate solutions, and respond to emerging business and technical challenges
Drive innovation by designing and developing reusable components, frameworks, and modern capabilities that teams can apply across applications
Stay current with advancements in Generative AI, LLMs, cloud technologies, and software engineering practices to identify opportunities that improve efficiency, automation, and outcomes
Work independently and collaboratively, demonstrating ownership, prioritization, and strong problem-solving
Support investment technology needs by building and maintaining applications and by designing, developing, and maintaining data flows between Trading, Accounting, and Datawarehouse platforms
Leverage cutting-edge technologies like Generative AI to increase productivity, streamline processes, and create seamless experiences for investment business groups

Requirements

5–7 years of hands-on software development experience
Solid understanding of the Software Development Lifecycle (SDLC)
Proficiency with Agile and Waterfall methodologies
Flexible mindset to work across different platforms and projects
Excellent written and verbal communication skills, able to collaborate effectively across teams and levels

Technology and skills

Languages & frameworks: Python, C#, .NET Core, Angular, TypeScript

AI/LLM engineering: AWS Bedrock, Claude, OpenAI, MCP

Cloud platforms: AWS Services (or Azure/GCP)

Data engineering: Oracle, SQL Server, PostgreSQL

Enterprise integrations: API development

Preferred skills: Financial Services / Investment Technology Domain Expertise

Department: Tech Data AI Ventures

Requisition ID: 95138

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2d ago

Data Analyst

U.S. Bank National Association New York, NY

New York, NY

2d ago

$93k - $109k/yr Full time Business Analytics Business Intelligence Data Analysis

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Job Description

Shape risk insights that leaders can act on. In this onsite Data Analyst role within Strategic Risk Analytics and Governance at U.S. Bank National Association, you will translate complex data into clear, actionable analysis across multiple financial risk disciplines. Expect to work in a governance-focused environment that emphasizes data quality, structured reporting, and continuous improvement, partnering closely with risk teams and senior stakeholders.

Salary range: USD 92,820 - 109,200 per year.
Location: New York, NY (onsite).
Onsite expectation: working from a U.S. Bank location three (3) or more days per week.

What you’ll do

Collect, organize, validate, and analyze data from multiple internal and external sources to support strategic financial risk analysis and governance activities.
Support cross-risk analysis across liquidity, interest rate risk, capital, market risk, regulatory reporting, and new or changing products.
Monitor data quality, investigate exceptions, document findings, and partner with data owners and risk teams to resolve issues.
Produce clear, concise presentations, governance reporting, and written analyses for risk committees and senior management.
Automate recurring data preparation and reporting processes where appropriate, while maintaining effective review and quality-control procedures.
Collaborate with Treasury, Balance Sheet Risk Management, and other business and risk partners.
Support ad hoc analyses, risk assessments, and strategic initiatives as needed.
Stay current on analytical techniques, data tools, financial risk trends, regulatory guidance, and industry practices, applying relevant insights to team deliverables.

What you bring

Bachelor’s degree, or equivalent work experience.
Typically more than five years of applicable experience (and three or more years in data analytics, financial risk management, banking, financial services, or a related field; equivalent education and experience may be considered).
Education background in areas such as Data Analytics, Finance, Economics, Statistics, Mathematics, Computer Science, Information Systems, or related fields (Bachelor’s degree or higher preferred).
Strong skills in SQL and advanced spreadsheet analysis; experience with Python, R, or a comparable analytical programming language is preferred.
Experience with data visualization and business intelligence tools such as Power BI or Tableau, plus Microsoft Office (including Excel and PowerPoint).
Ability to work with large or complex datasets, reconcile information across sources, identify data-quality issues, and document analytical logic and results.
Preferred understanding of banking and financial risk concepts, including liquidity, interest rate, capital, or market risk.
Familiarity with applicable banking laws, regulations, regulatory reporting, and risk-management expectations is a plus.
Strong analytical, problem-solving, organizational, and project-management skills with close attention to detail and accuracy.
Excellent written, verbal, interpersonal, and presentation skills, including explaining technical findings to non-technical audiences.
Intellectual curiosity, sound judgment, and a commitment to effective challenge, continuous improvement, and high standards of data integrity.

Tools you’ll use

SQL, Python, R, Power BI, Tableau, Microsoft Office, Excel, PowerPoint

Benefits

Healthcare (medical, dental, vision)
Basic term and optional term life insurance
Short-term and long-term disability
Pregnancy disability and parental leave
401(k) and employer-funded retirement plan
Paid vacation (from two to five weeks depending on salary grade and tenure)
Up to 11 paid holiday opportunities
Adoption assistance
Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law

Compliance and additional information

U.S. Bank participates in the U.S. Department of Homeland Security E-Verify program in all facilities located in the United States and certain U.S. territories.
U.S. Bank will consider qualified applicants with arrest or conviction records for employment.
Background checks are conducted consistent with applicable local laws, including the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act, as well as the San Francisco Fair Chance Ordinance.
Background checks are conducted consistent with requirements of Section 19 of the Federal Deposit Insurance Act (FDIA).
Certain positions may be subject to additional requirements such as FINRA, NMLS registration, Reg Z, Reg G, OFAC, the NFA, the FCPA, the Bank Secrecy Act, the SAFE Act, and/or other federal guidelines.
Applicants must comply with U.S. Bank policies and procedures, including the Code of Ethics and Business Conduct and related workplace conduct and safety policies.
Posting may be closed earlier due to high volume of applicants.

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2d ago

Machine Learning Engineer 5 (Senior Manager, IC)

Information Technology Senior Management Forum New York, NY

New York, NY

2d ago

$230k - $262k/yr Full time Backend Developer Manager Artificial Intelligence

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Job Description

Build and scale production-grade machine learning systems across modeling, data pipelines, and deployment practices.

Responsibilities

Design, build, and/or deliver ML models and components to address real-world business needs in collaboration with Product and Data Science
Develop and scale large multi-tenant platforms for ML model training and/or serving at scale
Guide ML infrastructure decisions using ML modeling expertise, including model and feature selection, training, hyperparameter tuning, dimensionality considerations, bias-variance tradeoffs, and validation
Solve complex problems through application code development, ML model development and validation, plus automated testing and deployment
Work in a cross-functional Agile team to create and enhance software supporting big data and ML applications
Retrain, maintain, and monitor machine learning models in production
Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Apply CI/CD best practices, including test automation and monitoring, to support successful deployment of ML models and application code
Manage code to reduce vulnerabilities, govern models from a risk perspective, and follow best practices for Responsible and Explainable AI
Use Python, Scala, or Java to implement ML and platform components

Requirements

Bachelor’s degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of programming experience with Python, Java, Golang, or C++
At least 6 years of ML experience with industry-standard frameworks PyTorch or Tensorflow, plus libraries (Pandas, NumPy, Scikit-learn)
At least 6 years operating large-scale distributed systems (e.g., Spark, Ray) to prepare AI/ML data
At least 4 years deploying and operating ML solutions in production and running production services in the cloud (AWS, GCP, Azure), using Kubernetes for large-scale containerized ML systems

Technologies

Python, Scala, Java, Golang, C++
PyTorch, Tensorflow
Pandas, NumPy, Scikit-learn
Spark, Ray
AWS, GCP, Azure
Kubernetes

Preferred Qualifications

Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
5+ years optimizing ML algorithms, configurations, and infrastructure
5+ years following software development best practices (source control, testing, code reviews, CI/CD)
5+ years building resilient software with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and incident response plan preparation
5+ years applying ML techniques (supervised, semi-supervised, unsupervised, reinforcement learning) across model types (Regression, Classification, Clustering), architectures (RNNs, CNNs, LSTMs, Transformers), and training concepts (loss function, hyperparameters, regularization), plus evaluating accuracy and diagnosing issues (underfitting, overfitting)
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
Ability to communicate complex technical and ML concepts clearly to varied audiences

Location: New York, NY (onsite)

Salary: USD 229,900 - 262,400 per yearly

Minimum experience: 4 years

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2d ago

Data Engineer 5

Capital One New York, NY

New York, NY

2d ago

$251k - $286k/yr Full time Backend Developer Apache Airflow Automation

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Job Description

Capital One seeks a Data Engineer 5 (Senior Manager, IC) to lead a major data transformation within Enterprise Data Tech (EDT). The role focuses on designing and delivering scalable, resilient, cloud-first data pipelines and platforms, using technologies commonly applied in the AI space.

Responsibilities

Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies
Influence a team of developers, data analysts, and data scientists with expertise across machine learning, distributed microservices, lakehouse architecture, and full-stack systems
Use programming languages including Python and Spark, along with open-source relational and NoSQL databases and cloud data warehousing platforms such as Databricks and Snowflake
Stay current with data technology trends through experimentation, learning new technologies, participating in internal and external technology communities, and mentoring members of the data community
Work with product managers and software engineers to deliver robust cloud-first data solutions that support experiences for millions of Americans seeking financial empowerment
Independently design, build, and deliver cloud data solutions and applications with little or no support from supervisors or managers
Architect and apply common data engineering design patterns to support code quality, maintainability, and reusability across platforms and pipelines
Design and build data pipelines and platforms emphasizing scalability, resilience, and operational efficiency, with performance under increasing data volume and business demand
Act as a force multiplier through a blend of hands-on technical contribution, innovation, mentoring, and elevation of peers and junior engineers
Lead and execute large-scale, transformative data initiatives end to end, including critical architectural decisions and platform evaluations such as Snowflake versus Databricks based on technical and business requirements
Serve as an ambassador for data engineering by communicating technical concepts and data outcomes clearly to internal and external stakeholders to drive alignment

Requirements

Bachelor's degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of experience in application development (internship experience does not apply)
At least 4 years of experience in distributed data
At least 4 years of experience with SQL
At least 4 years programming with Python, Java, or Scala
At least 4 years designing and developing data pipelines
At least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems

Technologies

Python, Spark
Databricks, Snowflake
SQL, NoSQL, relational databases
AWS, EMR, Glue
Lakehouse architecture, microservices
Redshift
MongoDB, Cassandra, DynamoDB
Airflow, Dagster
Monte Carlo, Splunk
Real-time, streaming data pipelines

Location

New York, NY (onsite)

Compensation

USD 250,800 - 286,200 per year

Benefits

Health, financial, and other benefits supporting total well-being
Performance-based incentive compensation, including cash bonus(es) and/or long term incentives (LTI)

Preferred Qualifications

Master’s degree in Computer Science or a related field
8+ years of experience in data engineering
5+ years of hands-on experience designing, deploying, and operating data workloads in AWS
5+ years of experience building or supporting distributed data or compute workloads using EMR, Spark, Glue, or Databricks
5+ years of experience designing, implementing, and operating real-time or streaming data pipelines
5+ years of experience working with unstructured or semistructured data using NoSQL databases (MongoDB, Cassandra, DynamoDB)
5+ years of experience designing and supporting data warehousing solutions (Snowflake, Redshift)
4+ years of data modeling experience
3+ years of experience working in an Agile development environment
3+ years of experience developing user-centric reusable data products
3+ years of experience working on data observability (Monte Carlo, Splunk) or data orchestration tools (Airflow, Dagster)