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Data Science Associate Jobs in East Brunswick, NJ

Associate Director, Data Science

New York, NY · On-site

$64K - $65K/yr

Data Science and AI PHD is a global communications planning and media buying agency network delivering smart strategic thinking and creative innovation for the world's leading brands. Brilliant media ...

Associate Director, Data Science

New York, NY · On-site

$64K - $65K/yr

Data Science and Analytics The Data Science team is pivotal in the delivery of modern agency services. We are tightly integrated with marketing science teams to deliver on and exceed our clients ...

Associate Director, Data Science

New York, NY · On-site

$64K - $65K/yr

Job Summary The Associate Director, Marketing Sciences is at the center of data, media and brand strategy. They act as a day-to-day contributor on specific client teams and focus on the generation of ...

Job Summary The Associate Director, Marketing Sciences is at the center of data, media and brand strategy. They act as a day-to-day contributor on specific client teams and focus on the generation of ...

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Data Science Associate information

See East Brunswick, NJ salary details

$57.2K

$67.7K

$128.4K

How much do data science associate jobs pay per year?

As of Aug 15, 2026, the average yearly pay for data science associate in East Brunswick, NJ is $67,714.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,700.00 and $59,200.00 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.

What can I do with a data science associate?

A data science associate typically supports data analysis, data cleaning, and model development using tools like Python, R, or SQL. They may assist in preparing reports, visualizations, and insights for decision-making, often working under the guidance of senior data scientists or analysts.

What is a data science associate?

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 are the key skills and qualifications needed to thrive as a data science associate?

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 East Brunswick, NJ?

The most popular types of Data Science jobs in East Brunswick, NJ are:

What job categories do people searching Data Science Associate jobs in East Brunswick, NJ look for?

The top searched job categories for Data Science Associate jobs in East Brunswick, NJ are:

What cities near East Brunswick, NJ are hiring for Data Science Associate jobs?

Cities near East Brunswick, NJ with the most Data Science Associate job openings:

Associate Director, Data Science

Princeton University

Princeton, NJ • On-site

$62K - $62K/yr

Full-time

Re-posted 16 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 618 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 Hours36.25Eligible for OvertimeNoBenefits EligibleYesProbationary Period180 daysEssential Services Personnel (see policy for detail)NoPhysical Capacity Exam RequiredNoValid Driver's License RequiredNo Experience LevelDirector#LI-JJ1Salary Range$145,000 to $160,000Employment Type: FULL_TIME

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