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Assistant Data Analytics Jobs in Delaware (NOW HIRING)

Examine data repositories and generate periodic reports to assist with resolution of consumer and ... Utilize SAS analytics and SAS Grid to design and create datasets from various sources including MS ...

Tealeaf Analyst-----Need GC and USC

Wilmington, DE · On-site

$80K - $80K/yr

... impact (field data, reporting, replay fidelity, etc.). Create custom Tealeaf events and ... practices. Assist in the performance of Tealeaf administration, optimization, planning, and ...

Senior Business Analyst

Dover, DE · On-site

$73K - $94K/yr

Perform data analysis, data mapping, and migration validation activities to ensure data integrity ... * Assist in development of training materials and support end-user training activities as the ...

Perform data analysis, data mapping, and migration validation activities to ensure data integrity ... * Assist in development of training materials and support end‑user training activities as the ...

Showing results 41-60

Assistant Data Analytics information

What is the difference between Assistant Data Analytics vs Data Analyst?

AspectAssistant Data AnalyticsData Analyst
Required CredentialsBachelor's degree in data science, statistics, or related fieldBachelor's or higher in data science, statistics, or related field
Work EnvironmentSupportive team, entry-level tasks, data collection and cleaningAnalyzing data, creating reports, providing insights
Employer & Industry UsageCommon in tech, finance, healthcare, and consulting firmsWidely used across industries for data-driven decision making

Assistant Data Analytics roles typically involve supporting data analysis tasks, focusing on data collection and cleaning, while Data Analysts perform in-depth analysis, generate reports, and provide strategic insights. Both roles require similar educational backgrounds, but Data Analysts usually have more experience and responsibilities.

What is an assistant data analytics?

Assistant Data Analytics professionals support data analysts and data scientists by preparing data, running basic analyses, and generating reports. They help collect, clean, and organize data so it can be used for business insights and decision-making. Their role often includes using spreadsheets, databases, and visualization tools to present findings clearly. This position is ideal for those starting in data analytics, as it offers hands-on experience with data processes and tools.

What does an assistant data analyst do?

An assistant data analyst supports data collection, cleaning, and analysis to help organizations make informed decisions. They often use tools like Excel, SQL, or data visualization software and may assist senior analysts with report preparation and data management tasks.

What are the key skills and qualifications needed to thrive as an assistant data analytics, and why are they important?

To thrive as an Assistant Data Analytics professional, you need strong analytical skills, a foundational understanding of statistics, and a relevant degree in fields such as mathematics, computer science, or economics. Familiarity with data analysis tools like Excel, SQL, and visualization software such as Tableau or Power BI is typically required. Attention to detail, problem-solving abilities, and effective communication are valuable soft skills for interpreting and presenting data insights. These skills and qualities are essential for supporting data-driven decision-making and ensuring accurate, actionable results in business environments.

What are some typical challenges faced by an assistant data analytics professional, and how can they be addressed?

Assistant Data Analytics professionals often encounter challenges such as managing large and sometimes incomplete datasets, prioritizing tasks among competing deadlines, and effectively communicating technical findings to non-technical team members. Building strong organizational skills and becoming proficient with data cleaning tools can help manage data quality issues. Regular collaboration with senior analysts and clear communication with stakeholders can also make it easier to navigate complex projects and bridge gaps between technical analysis and business insights.

What are the most commonly searched types of Data Analytics jobs in Delaware?

The most popular types of Data Analytics jobs in Delaware are:

What are popular job titles related to Assistant Data Analytics jobs in Delaware?

For Assistant Data Analytics jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Assistant Data Analytics jobs in Delaware look for?

The top searched job categories for Assistant Data Analytics jobs in Delaware are:

What cities in Delaware are hiring for Assistant Data Analytics jobs?

Cities in Delaware with the most Assistant Data Analytics job openings:

Infographic showing various Assistant Data Analytics job openings in Delaware as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Quant Analytics Associate I - Fraud Strategy

JPMorgan Chase & Co

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 14 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

71st of 171 rated banks


Job description

Drive impactful fraud prevention as a Quantitative Analytics Associate on our Point of Sale Fraud team-where your advanced risk analyses and strategic insights help reduce fraud losses, protect customers, and influence key decisions across the organization.

As a Quantitative Analytics Associate in the Point of Sale Fraud team, you will manage fraud risk strategies in the Fraud Policy area and perform complex risk analyses with the objective of reducing fraud related losses while balancing customer impact. You will frequently interact and communicate with cross-functional partners and communicate and present presentations to managers and executives.

Job Responsibilities:

  • Interpret large amounts of complex data to formulate problem statement, concise conclusions regarding underlying risk dynamics, trends, and opportunities
  • Manage, develop, communicate, and implement optimal fraud strategies (including rules, cutoffs, policies, operational flows, etc.) to protect the bank from fraud related losses and improve customer experience at Point of Sale
  • Identify key risk indicators and metrics, develop key metrics, enhance reporting, and identify new areas of analytic focus to better capture fraud.
  • Provide subject matter expertise on strategy implementation/testing and initiatives related to the improvement of risk mitigation processes and infrastructure
  • Collaborate with cross-functional partners to understand and address key business challenges
  • Identify business opportunity by performing well thought analysis - Data mining, ensuring data integrity, synthesizing and communicating findings to senior management
  • Assist team efforts in the critical development of new fraud pattern or spending pattern detection tools while providing clear/concise oral and written communication across various functions and levels, inclusive of Operations, IT, and Risk Management

Required Qualifications, Capabilities, and Skills:

  • Bachelor's degree (or related work experience) in a quantitative discipline in a financial services organization and 2 or more years' experience in fraud/risk/payments or related field.
  • Advanced understanding of Python, SAS, and SQL.
  • Ability to query large amounts of data and transform raw data into actionable management information.
  • Strong analytical and problem-solving abilities.
  • Experience delivering recommendations to management.
  • Self-starter with the ability to drive for resolution.
  • Strong communication and interpersonal skills with the ability to interact with individuals across departments/functions and with senior-level executives.

Preferred Qualifications, Capabilities, and Skills:

  • Master's degree (or related work experience) in a quantitative discipline, preferably in a financial services organization, plus 2 or more years' experience in fraud/risk/payments or related field.
  • Experience with Machine Learning technologies and knowledge of LLMs.

This role is not eligible for visa sponsorship. 

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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