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Data Science Major Jobs in New York (NOW HIRING)

Data Scientist

Manhattan, NY · On-site

$114K - $129K/yr

This is a "full-stack" data science role. You won't just build models in a notebook; you will ... For temporary assignments lasting 13 weeks or longer, AllSTEM Connections is pleased to offer major ...

Retail is in a state of major transition, and consumers have more options than ever. As a leading ... data science. This position resides in the Global Data Quality Management group. He or she will ...

Today, they work with a variety of major brands (such as Ulta Beauty, Budweiser, Flipkart, and more ... Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field ...

Data Scientist / Researcher

Manhattan, NY · On-site +1

$160K - $470K/yr

Graduated from or currently enrolled at a top-tier university, ideally with a degree or major related to data science. * Strong English writing & communication skills. * Excellent professional ...

Senior Lead Data Scientist

New York, NY · On-site

$204K - $226K/yr

In this role, you will have mastery over major organizational problems and solution spaces ... Deep expertise in multiple complex data science areas, such as XGBoost, deep learning, and NLP.

... architect major ML systems, mentor other scientists, and partner with engineering and product ... Ph.D. in Data Science, Machine Learning, Computer Science, Physics, Mathematics, Operations ...

Showing results 21-40

Data Science Major information

What is a data science major?

A Data Science major is an academic program that focuses on teaching students how to collect, analyze, and interpret large sets of data to solve real-world problems. It combines coursework in statistics, computer science, mathematics, and domain-specific knowledge to prepare graduates for roles in various industries such as technology, healthcare, finance, and more. Students learn programming languages like Python or R, machine learning techniques, and data visualization skills. The major often includes hands-on projects and internships to provide practical experience in analyzing and extracting insights from data.

What types of projects or problems do data science majors typically work on during internships or entry-level roles?

Data Science majors in internships or entry-level positions often collaborate on projects involving data cleaning, exploratory data analysis, and building predictive models. They might work with real-world datasets to identify trends, automate reporting, or support business decision-making with data-driven insights. These roles typically require teamwork with software engineers, business analysts, and domain experts, offering valuable opportunities to apply classroom knowledge to practical challenges and to develop skills in popular tools like Python, R, and SQL.

What are the key skills and qualifications needed to thrive as a data science major, and why are they important?

To thrive as a Data Science Major, you need a solid understanding of mathematics, statistics, and programming languages such as Python or R, typically backed by coursework or a related degree. Familiarity with data analysis tools, machine learning libraries, and platforms like SQL, TensorFlow, or Jupyter Notebook is also important. Critical thinking, effective communication, and problem-solving skills help you interpret data insights and collaborate on projects. These competencies enable you to extract meaningful information from data, drive decision-making, and succeed in a data-driven environment.

What is the difference between Data Science Major vs Data Analyst?

AspectData Science MajorData Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fieldsDegree in Statistics, Mathematics, or related fields
Work EnvironmentResearch, development, and complex data modelingData interpretation, reporting, and visualization
Industry UsageTech companies, finance, healthcare, academiaBusiness, marketing, finance, healthcare
Common Search/ComparisonData Science Major vs Data Analyst

While both roles involve working with data, a Data Science Major typically prepares individuals for complex data modeling, machine learning, and research tasks. In contrast, a Data Analyst focuses on interpreting data, creating reports, and visualizations to support business decisions. The roles often overlap, but the Data Science Major emphasizes advanced analytics and programming skills, whereas Data Analysts concentrate on data interpretation and communication.

What jobs can I do with a data science major?

A data science major can pursue roles such as data analyst, data scientist, machine learning engineer, business intelligence analyst, or data engineer. These positions typically require skills in programming, statistical analysis, and data visualization tools like Python, R, SQL, and Tableau, often with a focus on interpreting large datasets to support decision-making.

What kind of jobs can I get with a data science major?

A data science major can lead to roles such as data analyst, data scientist, machine learning engineer, business intelligence analyst, and data engineer. These positions typically require skills in programming, statistical analysis, and data visualization tools like Python, R, SQL, and Tableau.

What are popular job titles related to Data Science Major jobs in New York?

For Data Science Major jobs in New York, the most frequently searched job titles are:

What job categories do people searching Data Science Major jobs in New York look for?

The top searched job categories for Data Science Major jobs in New York are:

What cities in New York are hiring for Data Science Major jobs?

Cities in New York with the most Data Science Major job openings:

Infographic showing various Data Science Major job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Principal Scientist, Data Science (Translational Knowledge Engineering)

Johnson & Johnson

Raritan, NJ

Full-time

Retirement, PTO

Re-posted 17 days ago


Johnson & Johnson rating

8.3

Company rating: 8.3 out of 10

Based on 113 frontline employees who took The Breakroom Quiz

25th of 86 rated pharmaceutical


Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Horsham, Pennsylvania, United States of America, Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

About Innovative Medicine
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine

Position Summary

The Principal Translational Knowledge Architect & Graph Lead will be responsible for designing and implementing the semantic and knowledge architecture that enables AI-driven reasoning across the drug discovery and development lifecycle.

This role will serve as the scientific and technical lead for ontology development, knowledge graph design, semantic interoperability, and AI-ready knowledge representation. Working at the intersection of translational science, patient safety, biomedical informatics, and artificial intelligence, this individual will help establish the semantic foundation required to connect discovery biology, preclinical safety, clinical development, real-world evidence, and post-marketing safety into a unified reasoning framework.

The successful candidate will partner closely with scientists, safety experts, data scientists, AI engineers, and platform teams to create knowledge assets that support GraphRAG, agentic AI, scientific reasoning, and next-generation translational intelligence capabilities.

Mission

Build the semantic foundation that enables AI systems to reason across discovery, preclinical, clinical, and post-marketing domains while preserving scientific meaning, provenance, and translational fidelity.

Key Responsibilities

Semantic Architecture & Knowledge Modeling

  • Design and maintain enterprise knowledge models spanning:

    • Discovery biology

    • Toxicology

    • Safety pharmacology

    • Pathology

    • Clinical development

    • Pharmacovigilance

    • Real-world evidence

  • Develop semantic frameworks that support translational reasoning across the R&D lifecycle.

  • Create conceptual, logical, and physical knowledge models supporting AI-enabled scientific discovery.

Ontology Engineering & Governance

  • Lead ontology strategy, development, governance, and lifecycle management.

  • Curate and extend biomedical ontologies supporting translational safety and efficacy use cases.

  • Establish ontology governance processes, quality standards, and semantic review procedures.

  • Ensure semantic consistency, provenance, traceability, and FAIR data principles.

Knowledge Graph & Reasoning Infrastructure

  • Design RDF-based knowledge graph architectures and related semantic technologies.

  • Develop semantic mappings, inference rules, and reasoning frameworks supporting scientific decision-making.

  • Define knowledge representations enabling GraphRAG, semantic retrieval, AI agents, and reasoning systems.

  • Establish semantic interoperability across heterogeneous data sources and standards.

Translational Data Harmonization

  • Develop semantic bridges across major industry standards and ontologies, including:

    • SEND

    • SDTM

    • ADaM

    • MedDRA

    • HPO

    • MONDO

    • SNOMED CT

    • FHIR

    • OMOP

    • Cell Ontology

    • Protein Ontology

  • Enable AI systems to traverse translational boundaries while preserving biological and clinical context.

Scientific & Cross-Functional Leadership

  • Partner with stakeholders across Discovery, Preclinical Safety, Clinical Development, Pharmacovigilance, Data Science, and Digital Health.

  • Collaborate with engineering teams responsible for data products, pipelines, and AI platforms.

  • Influence enterprise semantic strategy and represent the organization in external standards and ontology communities when appropriate.

Required Qualifications

Education

  • PhD or Master's degree in:

    • Biomedical Informatics

    • Bioinformatics

    • Computational Biology

    • Computer Science

    • Information Science

    • Knowledge Engineering

    • Related scientific discipline

Experience

  • 5+ years of experience in biomedical informatics, semantic technologies, knowledge engineering, or scientific data architecture.

  • Demonstrated experience designing ontology-driven knowledge systems in life sciences, healthcare, or pharmaceutical R&D environments.

  • Experience working across multiple phases of drug discovery and development.

Technical Expertise

Deep expertise in:

  • Ontology development and governance

  • Knowledge representation

  • RDF

  • OWL

  • SHACL

  • SPARQL

  • Semantic Web technologies

Strong experience with:

  • Enterprise ontology management platforms

  • RDF graph architectures

  • Semantic APIs

  • FAIR data principles

Domain Knowledge

Strong familiarity with one or more of:

  • Translational science

  • Toxicology

  • Safety pharmacology

  • Clinical development

  • Pharmacovigilance

  • Regulatory data standards

Experience working with:

  • SEND

  • SDTM

  • ADaM

  • MedDRA

  • HPO

  • MONDO

  • FHIR

  • OMOP

Preferred Qualifications

  • Experience building semantic foundations for AI, GraphRAG, agentic AI, or scientific reasoning systems.

  • Familiarity with LLM-based retrieval and reasoning architectures.

  • Experience supporting translational safety, efficacy, biomarker, or mechanistic reasoning use cases.

  • Contributions to ontology standards, open-source biomedical ontologies, or scientific knowledge graph initiatives.

Leadership Competencies

  • Strategic thinker capable of translating scientific challenges into scalable knowledge architectures.

  • Strong communicator who can engage effectively with scientists, clinicians, data scientists, engineers, and senior leadership.

  • Ability to operate in ambiguous, highly cross-functional environments.

  • Passion for advancing AI-enabled drug discovery and development through semantic and knowledge-driven approaches.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.


Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
#LI-GR1
#LI-Hybrid
#JRDDS
#JNJDataScience
#JRD

Required Skills:

Preferred Skills:

Advanced Analytics, Coaching, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Digital Fluency, Econometric Models, Organizing, Process Improvements, Strategic Thinking, Technical Credibility, Workflow Analysis

The anticipated base pay range for this position is :

$117,000.00 - $201,250.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).
This position is eligible to participate in the Company's long-term incentive program.
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation -120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado -48 hours per calendar year; for employees who reside in the State of Washington -56 hours per calendar year
Holiday pay, including Floating Holidays -13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave - 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave - 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave - 80 hours in a 52-week rolling period10 days
Volunteer Leave - 32 hours per calendar year
Military Spouse Time-Off - 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits

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