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Data Scientist Python

New York,NY

921 Data Scientist Python jobs in New York,NY

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Head of AI Data Science, Intelligence Ventures

Spectrum

New York, NY 10036

OnsiteUrgently Hiring

  • 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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Principal Engineer - Python API Development

Fidelity Investments

Newark, NJ 07175

~ 28 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.
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Principal Engineer - Python API Development

Fidelity Investments

Harrison, NJ 07029

~ 23 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.
SmartExplore AI is experimental.
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New, Posted 5 hours ago
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Data Scientist

Canon USA

Old Westbury, NY 11568

$69,300-$103,770/yr
New, Posted 1 hour ago
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Manager, Economic Services - Data Science

KPMG

New York, NY 10025

OnsiteHealth InsuranceRetirement Benefit

  • Minimum of five years of recent experience with advisory related projects within a quantitative analysis firm, consulting firm, or background in a scientific laboratory
  • PhD in the areas of Computer Science, Mathematics, Mathematical Statistics, Electrical Engineering is required
  • A portfolio of projects (such as via GitHub, personal website, or other platforms) that demonstrates expertise in building and deploying AI/ML models and NLP solutions
  • Experience building data science or LLM-based products, with a demonstrable track record of your personal contributions to the codebase
  • Demonstrated experience in the development, application and interpretation of complex economic and statistical modeling frameworks using Python or R
  • Applicants must be authorized to work in the US 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 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 Careers

New York, NY 10025

Easy Apply
Business Development Manager, STEM Partnerships

Liberty Science Center

Jersey City, NJ 07305

~ 22 min OnsiteUrgently HiringHealth InsurancePaid Time OffRetirement Benefit

  • Valid driver's license (required)
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Head of Technology, Intelligence Ventures

Spectrum

New York, NY 10036

OnsiteUrgently Hiring

  • 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
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New, Posted 5 hours ago
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Data Scientist

Canon USA

Westbury, NY 11597

$69,300-$103,770/yr
New, Posted 17 hours ago
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Sr. Data / M/L Engineer [211066]

Skill

New York, NY 10261

Hybrid

  • Strong SQL and database management experience
  • Experience with data pipelines and ETL processes
  • Proficiency in machine learning and statistical modeling
  • Experience with BI tools (Power BI, Tableau)
  • Full-stack development knowledge
  • Experience with cloud platforms (AWS preferred)
  • Data architecture
  • Data modeling n
  • Infrastructure setup
  • Ability to work with large-scale datasets
  • Programming experience (likely Python/R inferred)
  • Strong problem-solving and analytical skills
  • Bachelor's degree in Electrical Engineering or Computer Engineering
  • The role requires full stack knowledge, including front-end and back-end components, and the ability to set up new infrastructure.
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