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Data Science Associate Jobs in New Jersey (NOW HIRING)

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Clinical Data Science Lead

Rahway, NJ · Hybrid

As a Clinical Data Science Lead at ICON, you will drive data science initiatives within clinical ... OR associate's degree with at least 5 years' professional experience in clinical data management;

Bayer

Associate Dir, Full Stack Data Scientist

Whippany, NJ · On-site +1

$59K - $59K/yr

The purpose of the Associate Director is to lead and deliver cross-functional Data Science capabilities enablement as a Full Stack Data Scientist in support of R&D Data Science needs for Bayer ...

Walmart

(USA) Principal, Data Scientist

Hoboken, NJ · On-site

Closely partner with the Senior Manager and Director of Data Science to drive data science adoption ... Partner and engage with associates in other regions to deliver the best services to customers ...

Walmart

(USA) Principal, Data Scientist

Hoboken, NJ · On-site

$132K - $264K/yr

You will work closely with agentic AI teams to build the data science capabilities, measurement ... part-time associates in Walmart and Sam's Club facilities. Programs range from high school ...

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Data Science Associate information

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$58.4K

$69.1K

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How much do data science associate jobs pay per year?

As of Aug 1, 2026, the average yearly pay for data science associate in New Jersey is $69,075.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,900.00 and $60,400.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

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

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

What are the key skills and qualifications needed to thrive as a Data Science Associate, and why are they important?

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

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

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in New Jersey? The most popular types of Data Science jobs in New Jersey are:
What are popular job titles related to Data Science Associate jobs in New Jersey? For Data Science Associate jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in New Jersey look for? The top searched job categories for Data Science Associate jobs in New Jersey are:
What cities in New Jersey are hiring for Data Science Associate jobs? Cities in New Jersey with the most Data Science Associate job openings:
Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in New Jersey as of July 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $69,075 per year, or $33.2 per hour.

Associate Director, Data Science

Princeton University

Princeton, NJ • On-site

$145K - $160K/yr

Full-time

Re-posted 27 days ago

Princeton University rating

9.0

Company rating: 9.0 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

26th of 614 rated colleges and universities

Job description

Overview
As part of University Advancement Data Strategy and Innovation team, the role of the Associate Director, Data Science is to turn data into tactical information and knowledge by applying statistical, algorithmic, mining and visualization techniques. Data Strategy and Innovation plays a critical strategic role within Advancement, providing the analytical framework, data architecture, application development, and tools for data-driven decision making at all levels of the organization.
The person in this role should be a creative thinker and propose innovative ways to look at problems that can be used to make sound organizational decisions. The Associate Director, Data Science will need to be able to present their findings and communicate data in ways that can be easily understood by their business counterparts. Working with the department Executive Director, this role will supervise the activities of the data science team and provide management of day to day functional operations. This position is a hands-on role, requiring active involvement in day-to-day technical operations, problem-solving, and project execution in addition to management responsibilities.In addition, this position will serve as a liaison to other teams within University Advancement - acting as a lead and driving strategic planning to successfully execute analytics strategies and solutions in support of the University fundraising and engagement operations.
Responsibilities
Statistical Modeling and Technical Exploration
  • Utilizing a combination of business focus, strong analytical and problem-solving skills and programming knowledge, drive new innovations and data exploration
  • Develop recommendation engines or automated lead scoring systems to drive our prospect management strategy and marketing segmentation, utilizing machine learning techniques
  • Work with structured data and drive innovation in unstructured data architecture and analysis
  • Work with statistical programming language, like R or Python, and database querying language like PL/SQL
  • Utilize innovative approaches to drive knowledge, incorporate and promote a big data environment.
  • Identify what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as social media and web analytics

Communication, Mentoring and Analytics Implementation
  • Work with business users to define desired outcomes and business requirements of analyses, data visualization and other reporting
  • Provide expertise on mathematical concepts for broader applied analytics and inspire the adoption of advanced analytics and data science across the Advancement Office
  • Describe findings or the way techniques work to audiences, both technical and non-technical, effectively using presentation tools such as data visualization, PowerPoint and documentation to drive strategic decision making and understanding of business analytics at all levels of the organization
  • Assist in addressing daily operational questions as needed, identify critical process improvement areas and collaborate in developing procedures and solutions for enhancing a high level of customer service

Staff Management
  • Serve as the team lead for projects and priorities of the data science team, working closely with the Executive Director, Prospect, Engagement, and Data Strategy to ensure projects are aligned with department and Advancement priorities
  • Responsible for the hiring and professional development of staff including training, mentoring, and identifying goals, objectives and metrics
  • Responsible for performance management of staff and monitoring of activity and metrics
  • Other related tasks as assigned

Best Practices & Strategy
  • Working closely with Data Strategy and Innovation team members, conceive of and contribute to strategies and best practices in maintaining a comprehensive, reliable, and innovative data environment
  • Review and recommend use of new technologies, vendor services and information sources. Keep abreast of news and relevant industry trends in support of the Office of Advancement
  • Develop and maintain proficiency in using advanced analytic and database tools, internet resources, in-house data, and other references

Qualifications
  • 7+ years of professional experience required in an analytical or information specialist role within an academic, nonprofit, corporate or consulting setting.
  • Deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms.
  • Keen desire to solve business problems, and to find patterns and insights within structured and unstructured data.
  • Expert in analyzing large, complex, multi-dimensional datasets with a variety of tools.
  • Accomplished in the use of statistical analysis environments such as R, MATLAB, SPSS or SAS.
  • Experience with BI tools such as Tableau.
  • Having a good understanding of relational databases, warehouse design and architecture principles.
  • Familiarity with big data frameworks (e.g., such as Hadoop, Hive, Spark).
  • Good scripting and programming skills (e.g. familiarity with SQL, Python, Java).
  • Strong foundation in statistical, mathematical, predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find effective answers.
  • Familiar with disciplines such as: natural language processing, machine learning, conceptual modelling, statistical analysis, predictive modeling and hypothesis testing.
  • Able to create examples, prototypes, demonstrations to help management better understand the work.
  • Able to work autonomously.
  • Proficiency at planning and setting meaningful objectives to meet office goals. Ability to articulate and promote goals and implement strategic plans.
  • Education: Bachelor's Degree in operations research, applied statistics, data mining, machine learning, or a related quantitative discipline required.

Preferred:
  • Knowledge of Princeton's mission
  • Experience in higher education
  • Master's degree or Ph.D. strongly preferred
  • Understanding of philanthropy (mission, practice, trends) and fundraising practices (the development cycle, prospect management policies and practices) preferred.

Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly.
If the salary range on the posted position shows an hourly rate, this is the baseline; the actual hourly rate may be higher, depending on the position and factors listed above.
The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
Standard Weekly Hours
36.25
Eligible for Overtime
No
Benefits Eligible
Yes
Probationary Period
180 days
Essential Services Personnel (see policy for detail)
No
Physical Capacity Exam Required
No
Valid Driver's License Required
No
Experience Level
Director
#LI-JJ1
Salary Range
$145,000 to $160,000

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