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Associate Data Science Analyst Jobs in Randolph, NJ

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 ...

Advanced Analytics & Insights: Develop and implement data science solutions, leveraging advanced analytics to drive data-driven decision-making, optimize business performance, and support Consumer ...

Senior Data Scientist

Bridgewater, NJ · On-site

$130 - $160/hr

Advanced Analytics & Insights: Develop and implement data science solutions, leveraging advanced analytics to drive data‑driven decision‑making, optimize business performance, and support ...

Showing results 41-60

Associate Data Science Analyst information

See Randolph, NJ salary details

$34.9K

$84.9K

$139.8K

How much do associate data science analyst jobs pay per year?

As of Aug 23, 2026, the average yearly pay for associate data science analyst in Randolph, NJ is $84,938.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,200.00 and $99,700.00 per year, depending on experience, location, and employer.

What does an associate data science analyst do?

An Associate Data Science Analyst is an entry-level professional who assists in collecting, analyzing, and interpreting data to help organizations make data-driven decisions. They work closely with senior data scientists and analysts, using statistical tools and programming languages like Python or R to process data, create reports, and visualize results. Their responsibilities often include cleaning and organizing data sets, performing exploratory data analysis, and supporting the development of predictive models. This role is a great way to gain hands-on experience in data science while building foundational skills for more advanced positions.

What are the key skills and qualifications needed to thrive as an associate data science analyst, and why are they important?

To thrive as an Associate Data Science Analyst, you need a solid grounding in statistics, data analysis, and programming languages such as Python or R, typically supported by a degree in a quantitative field. Familiarity with data visualization tools like Tableau, SQL databases, and potentially foundational certifications in data analytics are commonly required. Strong problem-solving, critical thinking, and effective communication skills help analysts interpret data insights and convey findings to stakeholders. These competencies are crucial for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

What types of projects and datasets do associate data science analysts typically work with, and how do they contribute to larger team goals?

Associate Data Science Analysts often work on projects involving data cleaning, exploratory analysis, and basic model development using real-world datasets such as sales figures, customer behavior logs, or operational metrics. Their primary responsibility is to prepare, analyze, and visualize data to uncover insights that support business decisions. They collaborate closely with more senior data scientists, business analysts, and stakeholders to ensure that their analyses align with organizational objectives. This role provides valuable exposure to the end-to-end data science workflow and lays the foundation for advancement into more specialized or senior data science positions.

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

AspectAssociate Data Science AnalystData Analyst
Required CredentialsBachelor's degree in data-related field; some roles prefer certifications in data analysis or programmingBachelor's degree in statistics, mathematics, or related field; certifications like Microsoft Excel or SQL are common
Work EnvironmentCollaborates with data scientists and engineers; involved in data modeling and analysis tasksFocuses on data collection, cleaning, and reporting; often works with business teams
Employer & Industry UsageUsed in tech, finance, healthcare industries; entry-level role in data teamsWidely used across industries for business insights and reporting

The Associate Data Science Analyst and Data Analyst roles share similarities in educational background and industry usage. However, the Associate Data Science Analyst typically involves more technical tasks like data modeling and working closely with data science teams, whereas Data Analysts focus more on data reporting and business insights. Both roles serve as entry points into data careers but differ in technical depth and collaboration scope.

What can I do with an associate data science analyst's degree in data science?

An associate data science analyst's degree prepares individuals for entry-level roles such as data analyst, data technician, or business intelligence assistant. These roles involve collecting, cleaning, and analyzing data using tools like Excel, SQL, and basic programming languages such as Python or R. The degree provides foundational skills for working in data-driven environments and can lead to further specialization or advancement in data science careers.

What cities near Randolph, NJ are hiring for Associate Data Science Analyst jobs?

Cities near Randolph, NJ with the most Associate Data Science Analyst job openings:

Principal Scientist, Data Science

Jj

Raritan, NJ • On-site

Full-time

Retirement, PTO

Posted 23 days ago


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