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Data Analyst Computer Science Jobs in Delaware (NOW HIRING)

SAP IBP Sr Analyst

Wilmington, DE · On-site

$160K - $175K/yr

The IBP Data and Technology Analyst will bring key system and process knowledge capabilities to the ... Bachelor's in Computer Science, Supply Chain or Engineering 10+ years of experience supporting ...

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Data Analyst Computer Science information

Is 40 too late for data science?

Data analysts and data scientists can successfully transition into the field at age 40 or older, as skills in programming, statistics, and data visualization are valuable regardless of age. Many professionals acquire relevant certifications or learn tools like Python, R, or SQL later in their careers to enhance their prospects.

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

To thrive as a Data Analyst in Computer Science, you need strong analytical skills, proficiency in statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with data analysis tools such as SQL, Python, R, and data visualization platforms like Tableau or Power BI, as well as experience with database systems, are typically required. Attention to detail, problem-solving abilities, and effective communication help data analysts translate complex data into actionable insights for stakeholders. These skills are crucial for accurately interpreting data trends, supporting business decisions, and driving organizational growth.

What is a Data Analyst in Computer Science?

A Data Analyst in Computer Science is a professional who collects, processes, and analyzes data to help organizations make informed decisions. They use various statistical tools and programming languages, such as Python, R, and SQL, to interpret complex datasets and identify trends or patterns. Their work often involves cleaning data, creating visualizations, and preparing reports for stakeholders. Data Analysts play a key role in turning raw data into actionable insights that drive business strategies.

How does a Data Analyst with a computer science background typically collaborate with other departments within a company?

Data Analysts with a computer science background often work closely with teams such as marketing, product development, and IT to translate raw data into actionable insights. They may participate in cross-functional meetings to understand business goals, provide data-driven recommendations, and help automate data collection processes. Strong communication skills are essential, as analysts must explain technical findings in a way that non-technical stakeholders can understand. This collaborative environment not only broadens their impact but also exposes them to various aspects of the business, fostering professional growth.

Can I be a data analyst with computer science?

Yes, a background in computer science provides a strong foundation for a data analyst role, as it covers programming, data structures, and algorithms. Data analysts often use tools like SQL, Excel, and statistical software, and having programming skills in languages such as Python or R is highly beneficial.

Is a data analyst a high salary?

Data analysts typically earn competitive salaries that vary based on experience, location, and industry. In general, they have higher-than-average starting pay compared to many entry-level roles, especially when skilled in tools like Excel, SQL, and data visualization software. Advanced skills or certifications can lead to higher compensation.

Will AI replace a data analyst?

AI can automate routine data processing and basic analysis tasks, but data analysts are essential for interpreting complex data, making strategic decisions, and providing context. The role of a data analyst involves skills like critical thinking, domain knowledge, and communication, which are difficult for AI to fully replicate. Therefore, AI is more likely to augment rather than replace data analysts in the foreseeable future.
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Data Science Vice President - Card Data Analytics

Data Science Vice President - Card Data Analytics

JP Morgan Chase

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 4 days ago


JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 487 frontline employees who took The Breakroom Quiz

55th of 146 rated banks


Job description

You can help shape how data and AI drive decisions across our Credit Card business. You will work on high-impact problems end-to-end-translating business questions into analytical approaches, building models and solutions, and communicating insights that influence strategy and outcomes. Join a collaborative team where your work can directly improve customer and business experiences through responsible, scalable analytics.

As a Data Science Vice President at JPMorganChase within the Card Data & Analytics team, you will develop analytics and AI/ML solutions that support strategic initiatives and measurable business impact. You will partner across the Card organization to define problems, scope solutions, and deliver high-quality analytical products. You will combine consulting, data science, and programming to drive data science and analytics strategies and deliver actionable insights.

Job responsibilities

  • Leverage experience and analytical skills to uncover novel use cases of Big Data analytics, including opportunities to responsibly apply foundation models and Generative AI
  • Drive data science and analytics strategies, including recommendations on analytical products and standards
  • Help partners define business problems and scope analytical solutions
  • Build an understanding of problem domains and available data assets
  • Research, design, implement, and evaluate analytical approaches and models, including Generative AI-based methods
  • Perform exploratory statistics and data mining tasks on diverse datasets
  • Communicate findings and obstacles to stakeholders to drive delivery to market
  • Develop subject matter expertise in financial and operational domains
  • Code solutions using strong programming skills
  • Collaborate across teams to deliver the best solutions for clients

Required qualifications, capabilities and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Bachelor's degree in a relevant quantitative field and 5+ years of data analytics experience, or advanced degree and 2+ years of experience
  • Exceptional analytical, quantitative, problem-solving, and communication skills
  • Intellectual curiosity for solving business problems
  • Leadership and collaboration skills
  • Knowledge of statistical software (for example, Python, R, SAS) and data querying languages (for example, SQL)
  • Familiarity with Generative AI and prompt engineering basics (prompt design, evaluation, guardrails)
  • Experience with modern analytics tools (for example, SAS, SQL, Hive, Hadoop, Spark, Python, Tableau, Alteryx)
  • Ability to convey complex information to technical and non-technical audiences

Preferred qualifications, capabilities and skills

  • Experience with large language model-enabled applications such as retrieval-augmented generation, classification or extraction from unstructured text, or agent-like workflows; exposure to evaluation methods for quality, cost, and latency
  • Understanding of key drivers within the credit card profit and loss statement
  • Financial services background
  • Master of Science degree or equivalent

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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