New York

Data Jobs in New York

144 jobs found

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Today

Lead Machine Learning Engineer

Capital One New York, NY

New York, NY

Today

$215k - $246k/yr Full time Ai Ml Artificial Intelligence Big Data

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Job Description

Capital One is hiring a Lead Machine Learning Engineer for an onsite role in New York, NY to design, develop, and productionize machine learning applications at scale.

Responsibilities

Design, build, and/or deliver machine learning models and components that address real-world business problems in collaboration with Product and Data Science teams
Drive ML infrastructure decisions using knowledge of modeling and training tradeoffs, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate on a cross-functional Agile team to create and enhance software for big data and ML applications
Retrain, maintain, and monitor models in production
Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale, including AWS and Kubernetes
Construct optimized data pipelines that feed ML models
Apply continuous integration and continuous deployment practices, including test automation and monitoring, to support successful deployment of model and application code
Maintain well-managed code to reduce vulnerabilities, ensure risk-governed models, and follow Responsible and Explainable AI best practices
Use programming languages such as Python, Go, Scala, or Java

Requirements

Bachelor’s Degree
6+ years designing and building data-intensive solutions using distributed computing (internship experience does not apply)
4+ years programming with Python, Scala, or Java
2+ years building, scaling, and optimizing ML systems

Technologies

Python, Go, Scala, Java
AWS, Kubernetes
scikit-learn, PyTorch, Dask, Spark, TensorFlow
Azure, Google Cloud Platform

Preferred Qualifications

Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
3+ years building production-ready data pipelines that feed ML models
3+ years on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
2+ years developing performant, resilient, and maintainable code using Python or Go
2+ years experience with data gathering and preparation for ML models
2+ years people leader experience
1+ years leading teams developing ML solutions using industry best practices, patterns, and automation
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
Experience designing, implementing, and scaling infrastructure using Kubernetes
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating performance
ML industry impact via conference presentations, papers, blog posts, open source contributions, or patents
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

Salary

USD 215,200 - 245,600 per year for New York, NY
Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

Location and Work Model

New York, NY (onsite)

Additional Information

Expected to accept applications for a minimum of 5 business days
No agencies please
Equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws
Drug-free workplace
Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws regarding criminal background inquiries
Accommodation request contact: 1-800-304-9102 or RecruitingAccommodation@capitalone.com
Technical support or recruiting process questions: Careers@capitalone.com
Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site
Work authorization: Capital One will not sponsor a new applicant for employment authorization or offer immigration-related support for this position
Capital One Financial includes multiple entities; location-based postings may correspond to different entities (e.g., Canada, UK, Philippines)

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Today

Marketing Data and Analytics Engineer

Fortune New York, NY

New York, NY

Today

$120k - $150k/yr Full time Marketing Application Support Business Systems

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Job Description

Fortune Media is building a marketing data foundation that connects CRM and marketing automation systems, with plans to expand into a broader CDP and ESP ecosystem. This role helps design and operationalize the pipelines, definitions, and governance needed for reliable measurement across Salesforce Sales Cloud and Salesforce Marketing Cloud.

Role Overview

You will design, build, and maintain data flows that connect Salesforce Sales Cloud and Salesforce Marketing Cloud, including Marketing Cloud Connect, while scaling the architecture to support future ESP and adjacent tooling (such as event platforms, subscription tools, and analytics layers). The role also creates the reporting and measurement frameworks used by marketing, editorial, events, and revenue operations stakeholders.

Key Responsibilities

Design, build, and maintain data pipelines between Salesforce Sales Cloud, Salesforce Marketing Cloud, and any future ESPs and adjacent systems (event platforms, subscription tools, analytics layers).
Ensure reliable, performant data synchronization within the integration architecture between Sales Cloud and Marketing Cloud Connect, and any future ESP and tools.
Evaluate and help implement future ESP and CDP tooling, defining how data enters, moves through, and exits each system.
Document all data flows, field mappings, and transformation logic in a centralized, accessible location.
Establish and maintain a data dictionary with canonical definitions for contacts, leads, accounts, subscribers, and audience segments across systems.
Enforce data quality standards including deduplication rules, field validation, consent flags, and suppression logic to support a unified customer “golden record.”
Partner with the Salesforce Developer to ensure custom objects, fields, and automations align with governance standards.
Maintain compliance hygiene for CAN-SPAM, GDPR, and opt-in/opt-out integrity across all marketing sends.
Build and maintain reporting frameworks for email performance, audience health, list growth, and data quality metrics.
Provide actionable insights to marketing and revenue stakeholders, including deliverability trends, segment performance, data decay, and contact coverage gaps.
Support attribution modeling and funnel reporting as Salesforce Sales Cloud and Marketing Cloud mature.
Act as an internal expert and translator between marketing operations, engineering, and business stakeholders on data questions.
Work with the Marketing Cloud Solutions Architect on technical implementation decisions.
Contribute to vendor evaluation and RFP processes as the team considers CDP and ESP investments.

Required Qualifications

Demonstrated ability to solve complex, high-scale engineering problems with clean, efficient code.
Strong proficiency in at least one major programming language (Python, Go, or Java) beyond basic scripting for data manipulation.
Expertise in designing scalable, fault-tolerant distributed systems.
Deep understanding of system design trade-offs (CAP theorem; latency versus throughput; synchronous versus asynchronous processing) in enterprise data pipelines.
Advanced data modeling knowledge beyond SQL, including NoSQL versus relational schemas and optimizing data structures for high-performance retrieval in a CDP or CRM environment.
2 to 6 years of experience in a data, data engineering, marketing operations, or martech-focused role.
Hands-on experience with Salesforce Sales Cloud and Salesforce Marketing Cloud, including understanding of how the systems connect and common failure points.
Fluency in SQL, with ability to query, transform, and validate data independently.
Working knowledge of data governance concepts including data dictionaries, lineage, deduplication, and master data management principles.
Experience designing or maintaining data integrations (APIs, connectors, ETL/ELT pipelines).
Strong documentation instincts that improve system clarity over time.
Comfort operating in ambiguity, with the roadmap being actively shaped.

Technologies

Python, Go, Java
SQL
Salesforce Sales Cloud, Salesforce Marketing Cloud
Marketing Cloud Connect
NoSQL
Relational schemas

Location and Compensation

Location: New York, NY (hybrid)
Salary: USD 120,000 to 150,000 per year
Minimum experience: 2 years

Benefits

20 vacation days and 2 personal days, plus 11 company holidays, and an honour-based sick leave policy.
Health, dental, and vision coverage (90% paid for individuals and families), with flexible spending accounts where Fortune contributes to your HSA.
401(k) plan.
Generous parental leave.
Dependent care, commuter, and cell phone benefits.
Tuition reimbursement program.
Commitment to an open, inclusive, and diverse work culture.

Preferred Qualifications

Experience with Marketing Cloud Connect and Synchronized Data Extensions.
Knowledge of email deliverability fundamentals (sender reputation, list hygiene, ISP feedback loops).
Exposure to ESP migration or evaluation projects.
Familiarity with CDP platforms (Salesforce Data Cloud, Segment, or similar) preferred.
Salesforce certification (e.g., Marketing Cloud Email Specialist, Administrator, or Data Cloud) preferred.
Experience in a media, publishing, or subscription business preferred.

Current Stack and Roadmap

CRM: Salesforce Sales Cloud
Marketing Automation: Salesforce Marketing Cloud
Integration: Marketing Cloud Connect
On the roadmap: CDP evaluation and integration; ESP consolidation or migration

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Today

Data Scientist

Mastercard New York, NY

New York, NY

Today

$138k - $221k/yr Full time Advanced Analytics Ai Ml Analytics

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Job Description

Build data products with real-world impact in Mastercard’s Loyalty group. This onsite Data Scientist role focuses on scalable, high-performance data platforms and predictive machine learning that supports personalized, card-linked offers. You will help deliver production-ready insights by turning analytics and model development into reliable workflows that business teams can use.

What you’ll do

Develop, validate, and deploy machine learning models for business use cases
Run exploratory data analysis (EDA) to identify trends, patterns, and actionable insights
Use statistical techniques to address complex business problems
Communicate findings clearly to stakeholders through visualizations and reports
Design and execute A/B tests and experiments
Build and maintain scalable data pipelines using ETL/ELT approaches
Work with large datasets in distributed environments
Maintain data quality, integrity, and reliability across systems
Optimize data workflows and processing performance
Partner with product, engineering, and business teams to define data-driven solutions
Translate business requirements into technical implementations
Deploy models into production and monitor model performance
Support best practices for documentation and reproducibility

What you bring

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field
Multiple years of professional experience in data science and/or data engineering roles
Strong programming skills in SQL and Python (required)
Hands-on experience with traditional machine learning frameworks such as scikit-learn, TensorFlow, and PyTorch
Experience building data pipelines with tools like Airflow and Spark
Solid understanding of statistics and probability

Tools you’ll use

SQL, Python, scikit-learn, TensorFlow, PyTorch, Airflow, Spark, ETL/ELT.

Security expectations

Abide by Mastercard’s security policies and practices
Ensure the confidentiality and integrity of the information being accessed
Report any suspected information security violation or breach
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines

Compensation and location

New York, NY (onsite): USD 138,000 - 221,000 per yearly.

Pay ranges also list San Francisco, California: USD 138,000 - 221,000 USD.

Benefits

Insurance including medical, prescription drug, dental, vision, disability, and life insurance
Flexible spending account and health savings account
Paid leaves including 16 weeks of new parent leave and up to 20 days of bereavement leave
80 hours of Paid Sick and Safe Time
25 days of vacation time and 5 personal days (pro-rated based on date of hire)
10 annual paid U.S. observed holidays
401k with a best-in-class company match
Deferred compensation for eligible roles
Fitness reimbursement or on-site fitness facilities
Eligibility for tuition reimbursement

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Today

AI Engineer

Persistent Systems New York, NY

New York, NY

Today

$133k - $166k/yr Full time Backend Developer Agentic Ai Analyst

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Job Description

Persistent Systems is hiring an AI Engineer in New York, NY (onsite) to design, build, test, deploy, and maintain secure AI applications. You will work across the full software development lifecycle, applying modern generative AI, RAG, and agent-based technologies to deliver production-ready solutions. This role includes building the engineering foundation for performance, cost, security, and reliability, alongside a team that values documentation, code review, and best practices.

What you’ll do

Design and maintain AI-powered applications from development through deployment and ongoing support
Develop RAG systems, AI agents, and conversational AI solutions
Partner with business, engineering, IT, security, and data teams to identify AI use cases and deliver solutions into production
Create secure data ingestion, retrieval, and search pipelines for AI workloads
Evaluate AI models, frameworks, SDKs, and cloud services based on performance, cost, security, and business needs
Build Python APIs and services using tools such as FastAPI, Docker, and Kubernetes
Implement AI safety, security, governance, and monitoring practices
Create evaluation frameworks to measure quality, accuracy, latency, cost, and reliability
Integrate AI solutions with enterprise databases and analytics platforms
Document solutions, mentor teammates, review code, and support engineering best practices

What you bring

2 to 5 years of experience in software engineering, machine learning, data engineering, or AI engineering
Bachelor’s degree in computer science, engineering, data science, mathematics, or a related field (or equivalent experience)
Strong Python programming skills
Experience building generative AI applications using LangChain, LangGraph, or similar frameworks
Experience with RAG, prompt engineering, and AI application development
Experience with at least one major AI platform: Azure AI Foundry, AWS Bedrock, Google Vertex AI, or Databricks
Familiarity with SQL and enterprise data systems
Strong communication and problem-solving skills
Ability to obtain or hold a U.S. Security Clearance

Tools you may work with

Python, SQL, pandas, R, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Microsoft 365 Agents SDK, OpenAI Agents SDK, Claude Agent SDK, Google ADK, Azure AI Foundry, AWS Bedrock, Google Vertex AI, Databricks, FastAPI, Docker, Kubernetes, CI/CD, Hugging Face, Ollama, LangSmith, MLflow, Braintrust, Langfuse, Arize Phoenix, Power BI, Tableau, PyTorch, TensorFlow, scikit-learn, XGBoost, Microsoft Copilot Studio, Power Platform, Azure Data Factory, AWS Glue, and MLOps/LLMOps.

Compensation and benefits

Salary: USD 133,000 - 166,000 per year.

Medical, dental, vision, life, and disability insurance
Paid time off (sick time and vacation time)
Flexible spending accounts
401(k) plan with company match
Fitness membership reimbursement
Tuition assistance
Mental health benefits
Pet discounts
Eligibility for yearly discretionary bonus

Preferred qualifications

Experience with multiple AI frameworks, cloud platforms, or agent SDKs
Experience deploying open-source models with Hugging Face or Ollama
Familiarity with FastAPI, Docker, Kubernetes, MLflow, and MLOps/LLMOps
Experience evaluating and monitoring AI systems in production
Knowledge of Power BI, Tableau, Microsoft Copilot Studio, or Power Platform
Data engineering experience with Azure Data Factory, AWS Glue, or Databricks
Experience with deep learning (PyTorch or TensorFlow) and traditional machine learning (scikit-learn, XGBoost)
Experience working in regulated or security-sensitive environments

Preferred certifications

Microsoft Azure AI certifications (AI-103, AI-200, AI-300)
AWS Certified Generative AI Developer – Professional
Google Cloud Professional Machine Learning Engineer
Databricks Certified Generative AI Engineer Associate

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Today

Data Engineer, GCS Data Science

Google New York, NY

New York, NY

Today

$106k - $151k/yr Full time Backend Developer Analytics Artificial Intelligence

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Job Description

Build scalable data pipelines and reporting tools on Google’s GCS Data Science team in New York, NY (onsite).

Responsibilities

Develop data pipelines, reporting assets, and reusable best practices/frameworks for analytics and stakeholder enablement across the organization.
Apply feature engineering to support ML/AI model development, including ETL pipeline development for downstream scaling.
Improve pipeline quality by adopting best practices for data integrity, test design, analysis, validation, and documentation.
Create scalable, actionable solutions including dashboards, automated collateral, and web applications that surface insights for advertisers.
Collaborate with stakeholders to identify feature and tooling gaps and drive customer-focused improvements.

Requirements

Bachelor’s degree in Computer Science or a related technical field (or equivalent practical experience).
At least 1 year of experience designing data pipelines (ETL) and model data.
Experience analyzing data and producing reports.
Experience with database query (for example, SQL) and visualization tools (for example, Tableau and dashboards).
Experience with one or more general purpose programming languages (for example, Python, C/C++, Java).

Technologies

ETL
ML/AI
SQL
Tableau
Dashboards
Python
C/C++
Java

Preferred Qualifications

Experience in a data science environment supporting feature engineering and model automation needs.
Experience with big data tools, distributed computing, and non-relational databases.
Structured thinking for breaking down ambiguous problems and proposing impactful data modeling designs.
Interest in analyzing large and complex datasets and translating findings into information that drives business decisions.

About the Role

The GCS Data Science team works on challenging problems for Google Customer Solutions (GCS) within Global Business Organization (GBO).
Goal: build efficient and scalable ML models to help small and midsize businesses grow using Google solutions.
The Data Science Engineering (DSet) subteam supports data engineering needs for GCS Data Science teams, including new data pipelines, automation, observability, and reporting tools.
Use an agile approach to tackle big data challenges and apply an analytical, data-driven method to understand a fast-changing business.
Build data pipelines and reporting tools that enable data scientists through feature engineering and automated data extracts and wrangling, delivering scaled insights for both the science team and users.
GCS sales teams focus on customer success for small- and medium-sized businesses (SMBs) by bringing Google solutions to customers.

Location and Compensation

Location: New York, NY (onsite)
Salary: USD 106,000 - 151,000 per year
Experience: 1+ years

Benefits

15% bonus target
Equity
Benefits
Health insurance
401k match

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Today

Data Engineer, Specialist Technology Team (STT), Centralized Data & Analytics

Amazon Web Services, Inc. New York, NY

New York, NY

Today

$132k - $197k/yr Full time Amazon Athena Amazon Emr Amazon Web Services

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Job Description

The AWS Specialist Technology Team (STT) is building a centralized analytics data platform to bring product telemetry, usage metrics, and business outcomes together in one place. In this Data Engineering role, you will design, build, and operate scalable ETL/ELT pipelines and data models that support agent-driven analytics experiences and executive decision-making.

You will join a high-growth engineering organization applying generative AI and agentic technologies to transform how AWS field teams operate, with the chance to help shape foundational architecture from the start.

What you’ll do

Design, build, and run scalable ETL/ELT pipelines to ingest product telemetry, usage events, and business outcome data from multiple heterogeneous sources across the STT product portfolio
Architect and implement a centralized data platform using AWS-native services, including Redshift, S3, Glue, Lake Formation, Lambda, and Athena, to serve as a single source of truth for organizational analytics
Build and maintain data models that connect product usage signals to business outcomes, including pipelines related to content effectiveness, field engagement, pipeline progression, and revenue impact
Develop data infrastructure for AI/ML pipelines and agentic systems, including MCP tools and natural-language data access layers
Implement data quality frameworks with automated monitoring, alerting, and validation to keep data accurate and reliable as the platform scales
Create self-service data products with defined SLAs, documentation, and governance to reduce ad-hoc requests and enable stakeholders to answer their own questions
Partner with Applied Scientists and SDE teams to deliver clean, well-modeled data for agent evaluation frameworks, retrieval quality measurement, and content effectiveness scoring
Establish data contracts, lineage tracking, and catalog metadata to improve discoverability and trust across the organization
Maintain operational excellence by owning on-call responsibilities, monitoring pipeline health, and resolving data freshness or quality issues before they affect consumers
Help evolve from static dashboards toward agentic data systems by building foundational data layers that AI agents can query and reason over

Requirements

3+ years of data engineering experience
3+ years developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
3+ years developing and operating large-scale data structures for business intelligence analytics using SQL
3+ years developing and operating large-scale data structures for business intelligence analytics using data modeling
3+ years of experience in the job offered or a related occupation

Technologies

Redshift, S3, Glue, Lake Formation, Lambda, Athena
ETL, ELT
SQL
EMR, Kinesis, FireHose
IAM roles and permissions
Natural-language data access layers, MCP tools

Preferred qualifications

Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases and data stores, including object storage, document or key-value stores, graph databases, or column-family databases

Benefits

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, with option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)

Location: New York, NY (onsite) • Compensation: USD 132,100 - 196,600 per year

About the team: You will be one of the first two Data Engineers on a centralized analytics team built from the ground up, working alongside Business Intelligence Engineers, a Senior BD, an Applied Scientist, and a TPM. The pace of innovation is high, problems are ambiguous, and the impact spans thousands of field team members and the customers they serve, with your work shaping how the organization consumes and acts on data.

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1d ago

Data Analyst

FocusKPI Inc. New York, NY

New York, NY

1d ago

$40+/hr Contract Analyst Analytics Business Intelligence

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Job Description

Contract Data Analyst role onsite in New York for five months focused on pricing operations, reporting, and analytics, with a pay rate of $40 per hour.

Responsibilities

Manage seller performance by creating and maintaining management dashboards and reports.
Generate targeted insights to inform the development of new seller offers.
Spearhead the deployment of pricing strategies within the client's pricing engine.
Test and review pricing configurations to confirm accuracy and proper functionality.
Identify, investigate, and resolve discrepancies uncovered during pricing system implementation.
Audit pricing data to verify accuracy and adherence to established guidelines.
Communicate effectively with team members and stakeholders about changes, updates, and issue resolutions in the pricing system.
Engage in day-to-day problem analysis, code execution, data analysis, and root-cause tracing to promptly address issues, including missed credits outside the crediting logic.

Requirements

3+ years of experience in operations, ideally in pricing operations, system implementation, or related roles in financial services.
Bachelor's degree in Business, Economics, Accounting/Finance, Computer Science, Math, Physics, Engineering, or other quantitative field.
SQL and Excel proficiency is mandatory.
Experience in coding and/or data visualization (for example Tableau).
Python experience is a plus.
Familiarity with business intelligence visualization tools.
CPA or CFA preferred.
Strong analytical and problem-solving skills with meticulous attention to detail.
Excellent communication and collaboration abilities for cross-functional teamwork.