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Computer Science Economics Jobs in New Jersey (NOW HIRING)

D. degree in a quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar), * 5+ ...

About You Experience & Expertise Degree qualified in a relevant technical discipline (Data Science, Computer Science, Engineering, Mathematics, Statistics, Econometrics, or similar). Proven ...

Bachelor's Degree in Data Science, Computer Science, Mathematics, Statistics, Economics or related fields required or equivalent years of experience. * Master's Degree in Computer Science ...

D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines • Working on complex problems in which analysis ...

Bachelor's Degree in Data Science, Computer Science, Mathematics, Statistics, Economics or related fields required or equivalent years of experience. * Master's Degree in Computer Science ...

Build statistical and econometric models for various problems including: projections, clustering ... computer science, Public Health or other highly quantitative discipline is required 10+ years in ...

Principal Data Science Engineer

Basking Ridge, NJ · On-site

$118K - $141K/yr

A master's degree in a quantitative discipline such as Mathematics, Statistics, Financial Economics/Econometrics, Engineering, Computer Science, or Operations Research. * Hands-on experience ...

Showing results 21-40

Computer Science Economics information

See New Jersey salary details

$11.2K

$99.5K

$162.9K

How much do computer science economics jobs pay per year?

As of Aug 11, 2026, the average yearly pay for computer science economics in New Jersey is $99,493.00, according to ZipRecruiter salary data. Most workers in this role earn between $22,300.00 and $162,400.00 per year, depending on experience, location, and employer.

What does a computer science economics do?

Professionals in Computer Science Economics roles blend data analysis, economic modeling, and software development to provide insights that guide business strategies and policy decisions. On a typical day, you might analyze large datasets, build predictive economic models, collaborate with data engineers or economists, and present findings to stakeholders. Many roles are highly collaborative, often involving teamwork with both technical and non-technical colleagues to solve complex, real-world business or economic problems. The work environment can range from consulting firms to financial institutions or tech companies, offering a dynamic and intellectually stimulating setting with opportunities for continued learning and career growth.

What is a computer science economics?

A Computer Science Economics job combines computing, data analysis, and economic principles to solve complex business and financial problems. Professionals in this field work with algorithms, machine learning, and economic models to analyze trends, optimize decision-making, and improve efficiency. They may work in industries like finance, tech, or policy analysis, using data-driven methods to drive insights and innovation.

What skills and qualifications are needed for a computer science economics?

To excel in a Computer Science Economics role, candidates typically need a strong background in both computer science fundamentals (such as programming, algorithms, and data structures) and economic theory, often evidenced by degrees in these or related fields. Familiarity with analytical tools like Python, R, SQL, and statistical modeling software, as well as experience with data visualization platforms, are commonly required. Strong communication, critical thinking, and problem-solving abilities enable effective collaboration across multidisciplinary teams. These skills and qualifications are crucial for leveraging computational techniques to analyze complex economic data and deliver actionable insights in technology-driven industries.

What can you do with a computer science and economics degree?

A computer science and economics degree prepares individuals for roles such as data analyst, financial analyst, software developer, or economic consultant. Graduates can work in finance, technology, consulting, or research, often utilizing skills in programming, data analysis, and economic modeling.

Is computer science and economics a good combination?

Computer Science Economics combines technical programming skills with economic analysis, making it valuable for roles in data analysis, financial modeling, and tech-driven economic research. This interdisciplinary background can enhance job prospects in finance, consulting, and technology sectors that rely on data-driven decision making.
What are popular job titles related to Computer Science Economics jobs in New Jersey? For Computer Science Economics jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Computer Science Economics jobs in New Jersey look for? The top searched job categories for Computer Science Economics jobs in New Jersey are:
Infographic showing various Computer Science Economics job openings in New Jersey as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 14% Part Time, 2% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $99,493 per year, or $47.8 per hour.

Principal Scientist, Data Science

Johnson & Johnson

Titusville, NJ

Full-time

Retirement, PTO

Posted 12 days ago


Johnson & Johnson rating

8.3

Company rating: 8.3 out of 10

Based on 112 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, Raritan, New Jersey, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

J&J Innovative Medicine - Data, Data Science, and AI - Global Development (DDSAI GD) is recruiting a Principal Scientist. The ideal candidate will Lead analytics, ML, optimization, and GenAI that rely primarily on realworld data to inform clinical trial design, feasibility, and execution facilitation, translate insights from RWD sources (e.g., EHR, claims, registries, digital health) into clear recommendations that shape protocol decisions and operational plans.

J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market - from patients to practitioners and from clinics to hospitals. To learn more about J&J Innovative Medicine, visit https://www.jnj.com/innovative-medicine

Key responsibilities:

  • Use RWD to quantify disease prevalence, care pathways, and the impact of inclusion/exclusion criteria; produce feasibility scoring across geographies, sites, and subpopulations.

  • Assess RWDfeasible endpoints and proxies; evaluate availability, completeness, quality, and signaltonoise to guide protocol design choices.

  • Construct RWDbased cohorts and external/synthetic controls to benchmark protocol decisions and stresstest samplesize/timeline assumptions.

  • Develop ML and multiobjective optimization solutions primarily powered by RWD to surface tradeoffs (speed, quality, cost, diversity) and recommend design and operational scenarios informed by realworld care patterns.

  • Build RWDcalibrated stochastic simulations of patient journeys to forecast timeline sensitivities and completion risk; provide RWD features, calibration sets, and feasibility constraints to the partner team's enrollment/screenfailure/retention models.

  • Adapt LLMs/GenAI for structured extraction from RWD artifacts (structured and unstructured EHR, notes, radiology/pathology reports, claims, registries); harmonize concepts to standard vocabularies to support eligibility criteria evaluation and scheduleofactivities insights grounded in realworld practice.

  • Clearly communicate RWDbased assumptions, methods, and results to clinical, operational, and leadership stakeholders; coach and mentor colleagues on RWD methodologies, pipelines, and best practices.

Required qualifications:

  • A Ph.D. degree in quantitative discipline (e.g., computer science, electrical and computer engineering, biostatistics, health economics, biomedical informatics, applied mathematics, or similar),

  • 5+ years delivering ML/NLP/GenAI and multi objective optimization solutions with primary reliance on RWD (EHR, claims, registries, digital health), including collaboration with operations analytics teams.

  • Hands on experience with multimodal RWD (structured + unstructured) predictive modeling and stochastic simulations for feasibility and time series scenario forecasting.

  • Demonstrated ability to construct, validate, and deploy models from RWD to inform trial feasibility, endpoint selection, eligibility criteria effects, and external control design.

  • Experience building optimization engines (e.g., evolutionary algorithms, reinforcement learning, mixed integer linear programming) using RWD derived signals to navigate complex tradeoffs.

  • Proficiency in MLOps (e.g., MLflow, Kedro), Git, and CI/CD; strong programming skills in Python and SQL; familiarity with DSPy/LangChain, pymoo, scikit learn, XGBoost, Optuna, PyMC.

  • Familiarity with healthcare privacy/compliance, de identification practices, and RWD data quality management; ability to integrate outputs from operational systems/models when needed while keeping the analytical core RWD driven.

Preferred qualifications:

  • Demonstrated expertise applying RWD methods to inform trial design: target trial emulation, propensity weighting/matching, and survival/timetoevent analyses for endpoint feasibility and external/synthetic controls.

  • Proven collaboration with operations analytics teams by supplying RWDderived cohorts, features, and feasibility evidence that improved enrollment forecasting, site selection, and diversity goals.

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 and 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, please email the Employee Health Support Center (ra-employeehealthsup@its.jnj.com) or 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)).
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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