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Phd Library Science Jobs in New York (NOW HIRING)

Vola Dynamics LLC

Quant Researcher

New York, NY · On-site

$175K - $250K/yr

You hold a PhD degree in a hard science or mathematics. * You have a proven track record of ... library or framework. * You have significant experience using the scientific Python stack ...

GDR Defense

Sr. Data Researcher || 100% REMOTE

New York, NY · On-site

$140K - $160K/yr

Education / Training / Libraries Job Category: Information Technology - Business Intelligence ... Ideal Candidate PhD in Computer Science, or similar fields Background in relational databases, big ...

New

Point72

Machine Learning Engineer

New York, NY

PhD or PhD candidate in machine learning, computer science or other AI related research fields ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

Point72

Machine Learning Engineer

New York, NY · On-site

PhD or PhD candidate in machine learning, computer science or other AI related research fields ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

Carlyle

AlpInvest Embedded Data Scientist

New York, NY · On-site

$190K - $220K/yr

  • Medical

  • Life

  • Retirement

  • PTO

Bachelor's degree or higher (MS, PhD, MBA, or equivalent), required * Concentrations in Data ... Strong programming skills in Python and experience with modern data science libraries and ...

Targeted Talent

Principal systems software engineer

New York, NY · On-site

$147K - $198K/yr

  • Medical

  • PTO

Masters or PhD in Computer Science, Computer Engineering or a related discipline * Experience with Python and using C/C++ libraries from Python (e.g. using Cython) * Focus on software quality and ...

Targeted Talent

Principal systems software engineer

New York, NY · On-site

$147K - $198K/yr

  • Medical

  • PTO

Masters or PhD in Computer Science, Computer Engineering or a related discipline * Experience with Python and using C/C++ libraries from Python (e.g. using Cython) * Focus on software quality and ...

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Phd Library Science information

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How much do phd library science jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for phd library science in New York is $17.22, according to ZipRecruiter salary data. Most workers in this role earn between $12.88 and $19.18 per hour, depending on experience, location, and employer.

What cities in New York are hiring for Phd Library Science jobs?

Cities in New York with the most Phd Library Science job openings:

Phd Library Science jobs near you
Infographic showing various Phd Library Science job openings in New York as of June 2026, with employment types broken down into 32% Full Time, 65% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $35,810 per year, or $17.2 per hour.

Applied AIML Data Scientist Lead - Vice President

JPMorgan Chase & Co.

Jersey City, NJ • On-site

$130 - $160/hr

Other

Re-posted 20 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description

The Legal Applied AI/ML team in Corporate Technology at JPMorgan Chase focuses on solving challenging business problems such as semantic search, question answering, document analysis, automation of service inquiries through data science and ML techniques, particularly using GenAI and LLM tools and techniques. You will work with the firm’s rich data pool from both internal and external sources using GenAI tools and frameworks, Python/Spark via AWS and other systems. You are also expected to derive business insights from technical results and be able to present them to non-technical audience.

As an Applied AI ML Data Scientist Lead‑Vice President on Corporate team, you will have the opportunity to study complex business problems and apply advanced algorithms to develop, test, and evaluate AI/ML applications or models for those problems.

Job responsibilities
  • Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases.
  • Develop GenAI and LLM solutions to solve business problems.
  • Implement optimization strategies to fine‑tune generative models for specific GenAI use cases, ensuring high‑quality outputs.
  • Execute tasks throughout a model development process including data wrangling/analysis, model training, testing, and selection.
  • Generate structured and meaningful insights from data analysis and modelling exercise and present them in appropriate format according to the audience.
  • Communicate AI/GenAI capabilities and results to both technical and non‑technical audiences.
  • Stay informed about the latest trends and advancements in AI research, implement cutting‑edge techniques, and leverage external APIs for enhanced functionality.
Required qualifications, capabilities, and skills
  • PhD in Computer Science or a related quantitative discipline with 2+ years of relevant experience or MS/BS in Computer Science or a related field with 4+ years of relevant experience.
  • Practical expertise with LLM projects as well as other supervised and unsupervised techniques; proven track record of deploying AI/ML applications in a production environment.
  • Proficient programming skills with Python and SQL as well as practical experience with other languages such as R, Java and other equivalent languages.
  • Demonstrated experience working with large and complicated datasets.
  • Experience with ML frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit‑learn, and OpenAI API.
  • Experience integrating user feedback to establish agentic refinement and self‑improving AI applications.
  • Solid understanding of fundamentals of statistics and machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning) and generative model architectures, particularly Transformer.
  • Ability to identify and address AI/LLM challenges, implement optimizations and tune models for optimal performance in NLP applications.
  • Excellent problem solving, communication (verbal and written), and teamwork skills.
Preferred qualifications, capabilities, and skills
  • Experience working with engineering teams to operationalize ML models.
  • Expertise in designing and implementing pipelines using RAG and Agentic AI framework.
  • Hands‑on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
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