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Phd Library Science Jobs in New York (NOW HIRING)

Prior Labs

Applied Scientist, Data Science

New York, NY · On-site

PhD or Master's in a quantitative field, plus 3+ years of experience building and deploying ML/AI ... Contributions to open-source libraries or data science tooling * A portfolio of blog posts, talks ...

Ramp

Senior Applied Scientist, Credit Risk

New York, NY · Remote

$165K - $228K/yr

... or similar libraries * Strong communication: the ability to bridge technical methodology to ... PhD in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other ...

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Phd Library Science information

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$9

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$31

How much do phd library science jobs pay per hour?

As of Jul 26, 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.

Data Scientist ::Onsite in NYC, NY (Onsite)

Talent Movers

New York, NY • On-site

Contractor

Posted 28 days ago

Job description

Title : Data Scientist

Location: Onsite in NYC, NY (Onsite)

Rate: ON C2C/W2

 

Top 3 must-have HARD skills:

Experience with hardware sensors and real-world data analysis
Direct experience working with biosensors or similar hardware, and analyzing the resulting data.
Signal processing expertise
Ability to process time domain signals and/or medical imaging systems, which is crucial for biosensor data.
Advanced programming and data manipulation
3+ years of hands-on experience with Python, R, MATLAB, or SQL for data extraction, manipulation, and visualization, including proficiency with scientific computing and analysis packages (NumPy, SciPy, Pandas, Scikit-learn, etc.).

Good to have skills:

Experience presenting findings from statistical and machine learning methods to diverse audiences.
Proficiency in data structures and algorithms.
Experience with data visualization libraries (Matplotlib, Pyplot, seaborn, ggplot2).
Experience working with large datasets.
Familiarity with scientific computing and analysis packages (dplyr, caret).
Advanced degree (Master’s or PhD) in computer science, statistics, neuroscience, biomedical engineering, or related field.

Job Description:

Summary:
The main function of the Data Scientist is to produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. The Data Scientist will contribute to biosensor data analysis and help to guide future biosensing R&D.
Job Responsibilities:
Execute, debug, and optimize distributed compute workflows for metric computation, analysis, and modeling across large datasets.
Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, and make valuable discoveries leading to prototype biosensor development and product improvement.
Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the biosensor data.
Generate and test hypotheses and analyze and interpret the results of product experiments.
Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation.
Leverage data visualization to help the team make decisions about future R&D directions to go.
Skills:
Experience with hardware sensors, and data analysis pertaining to real-world data.
Experience with signal processing pertaining to time domain signals and/or medical imaging systems
Experience presenting findings from statistical and machine learning methods to diverse audiences
Experience working with large datasets.
3+ years of experience performing data extraction, manipulation, and visualization using programming languages (e.g., Python), scientific computing languages (e.g., R, MATLAB), or SQL.
Proficiency in data structures and algorithms.
Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, caret.
Experience with data visualization libraries such as Matplotlib, Pyplot, seaborn, ggplot2.
Education/Experience:
Master of Science or PhD degree in computer science, statistics, neuroscience, biomedical engineering, or other relevant field.