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Data Science Research Assistant Jobs in Delaware

We clear the way by pairing exceptional Executive Assistants with our driven clients, providing ... Role Overview The Data Science Intern will help us to understand the performance of Executive ...

We clear the way by pairing exceptional Executive Assistants with our driven clients, providing ... Role Overview The Data Science Intern will help us to understand the performance of Executive ...

Manager, Data Science Location: Wilmington, DE (Hybrid) We are seeking a Manager to join our Data ... Research and develop new modeling techniques that will keep OneMain at the forefront of the ...

The Director, Data Science - Competitive Intelligence, AI Insights & Strategic Analytics is a ... Design and implement AI-powered market intelligence and competitive research solutions that ...

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Data Science Research Assistant information

See Delaware salary details

$8

$21

$31

How much do data science research assistant jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for data science research assistant in Delaware is $21.93, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $25.48 per hour, depending on experience, location, and employer.

Is 30 too late for data science?

Data science research assistants can enter the field at any age, including 30, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is less important than demonstrated competence and ongoing development in the field.

What does a Data Science Research Assistant do?

A Data Science Research Assistant supports research projects by gathering, cleaning, and analyzing data using statistical and computational techniques. They assist senior researchers with designing experiments, developing models, and interpreting results. Typical tasks include data preprocessing, coding in languages like Python or R, literature reviews, and creating visualizations to summarize findings. Their work helps advance scientific knowledge and inform decision-making based on data-driven insights.

What is the difference between Data Science Research Assistant vs Data Analyst?

AspectData Science Research AssistantData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's or higher in Data Analysis, Statistics, or related field
Work EnvironmentResearch labs, academic institutions, or research-focused organizationsBusiness settings, corporate offices, or consulting firms
Employer & Industry UsageUniversities, research institutes, government agenciesCorporations, marketing firms, finance, healthcare
Common Search & ComparisonYesNo

Data Science Research Assistants typically focus on supporting research projects through data collection, analysis, and modeling in academic or research settings. Data Analysts primarily interpret data to help organizations make business decisions. While both roles require strong analytical skills and knowledge of data tools, the research assistant role emphasizes academic research and experimentation, whereas data analysts focus on business insights and reporting.

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

To thrive as a Data Science Research Assistant, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, statistics, or related fields). Familiarity with tools such as Python, R, Jupyter Notebooks, and data visualization libraries as well as experience with version control systems like Git is typical, and coursework or certifications in data science can be beneficial. Attention to detail, problem-solving ability, and strong communication skills are essential to effectively analyze data, interpret results, and collaborate with research teams. These skills and qualities are critical for producing reliable insights, supporting research objectives, and ensuring the integrity of data-driven projects.

Is AI replacing data scientists?

AI is transforming the role of data science research assistants by automating routine tasks like data cleaning and analysis, but it does not replace the need for human expertise in designing models, interpreting results, and making strategic decisions. Data scientists and research assistants with skills in programming, statistical analysis, and machine learning remain essential for developing and deploying AI solutions effectively. AI tools serve as complements that enhance productivity rather than substitutes for skilled data professionals.

Is 40 too late for data science?

Age is not a barrier to becoming a data science research assistant; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be developed through online courses, certifications, and practical experience regardless of age.

How do Data Science Research Assistants typically collaborate with other team members during a research project?

Data Science Research Assistants frequently work alongside data scientists, research leads, and subject matter experts to support ongoing research. Their responsibilities often include cleaning and preprocessing data, performing exploratory analyses, and implementing models. Regular collaboration occurs through team meetings, code reviews, and sharing findings, ensuring alignment with project goals. Open communication and adaptability are essential, as priorities and datasets can shift based on project needs.

What is a data research assistant?

A data research assistant is a professional who supports data collection, analysis, and interpretation for research projects. They often work with statistical tools and programming languages like Python or R and may assist in preparing reports or visualizations under the guidance of senior researchers.
What cities in Delaware are hiring for Data Science Research Assistant jobs? Cities in Delaware with the most Data Science Research Assistant job openings:
Infographic showing various Data Science Research Assistant job openings in Delaware as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $45,610 per year, or $21.9 per hour.
Quant Analytics Associate - Card Data Anaytics

Quant Analytics Associate - Card Data Anaytics

JPMorgan Chase & Co

Wilmington, DE

$57K - $57K/yr

Full-time

Medical, Retirement

Posted 11 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 492 frontline employees who took The Breakroom Quiz

71st of 170 rated banks


Job description

Description

We're driven by curiosity, passion, optimism, and the belief that everybody can grow.

The Data Science Associate, Card Lending & Strategic Analytics, is a unique opportunity for a well-rounded data analytics professional to leverage data science methods and analytics to deliver actionable customer insights and data-driven solutions across the Card business.

As a Data Science Associate within the Card Lending & Strategic Analytics team, you will leverage your skills in building analytics, analysis, data querying, and extracting customer insights from big data to support our Credit Card business. This role is a hands-on mix of consulting know-how, analytical proficiency in statistics, data science, proficiency in SQL/Python programming, visualization methods, and technologies. You will have the opportunity to leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics that can be deployed at scale across the Credit Card business.

Job Responsibilities:

  • Work with partners across Card Strategy and Lending to provide data insights and support portfolio strategies.
  • Help partners in the Card business define their problems, understand root causes, and scope analytical solutions - uncovering novel, scalable use cases of Big Data analytics across the Credit Card business.
  • Build an in-depth understanding of the Card domain and available data assets.
  • Research, design, implement, and evaluate analytical approaches and models, including ad-hoc exploratory analyses and data mining across small-scale to "big data" datasets.
  • Take initiative in evaluating and adapting new approaches from data science research.
  • Investigate data visualization and summarization techniques, and communicate findings and obstacles to stakeholders to drive delivery to market.
  • Code your solutions (this is a hands-on position requiring exceptional programming skills).
  • Leverage AI agents and LLM-based tools to streamline analyses and automate the generation of insights, documentation, and reporting narratives.
  • Collaborate across teams to deliver the best solution for the client, working with a wide range of internal resources.

Required qualifications, capabilities, and skills:

  • Bachelor's degree in relevant quantitative field required.
  • 2+ years of hands-on experience with data analytics; experience evaluating complex business problems, data analysis and devising recommendations and analytics to solve those business problems.
  • Exceptional analytical, quantitative, problem solving, and communication skills.
  • Excellent leadership, consultative partnering and collaboration across teams.
  • Knowledge of statistical software and modern analytics tools (e.g., Python, R, SAS, SQL, Hive, Hadoop, Spark, Tableau, Alteryx).
  • Ability to convey complex information in an understandable, compelling, and persuasive manner to both technical and non-technical audiences.

Preferred qualifications, capabilities, and skills:

  • Advanced degree preferred in analytical field (e.g. Statistics, Economics, Applied Math, Operations Research, other Data Science fields)
  • Understanding of the key drivers within the credit card P&L is preferred.
  • Financial services background preferred, but not required.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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