1

Scientific Machine Learning Jobs in Delaware (NOW HIRING)

... Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis • Partner with leads in Data Science, Engineering, and Analytics to ...

Role Overview The Data Science Intern will help us to understand the performance of Executive ... Strong foundation in statistics and machine learning concepts (regression, classification ...

Role Overview The Data Science Intern will help us to understand the performance of Executive ... Strong foundation in statistics and machine learning concepts (regression, classification ...

next page

Showing results 1-20

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Delaware? For Scientific Machine Learning jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Delaware look for? The top searched job categories for Scientific Machine Learning jobs in Delaware are:
What cities in Delaware are hiring for Scientific Machine Learning jobs? Cities in Delaware with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Delaware as of July 2026, with employment types broken down into 81% Full Time, 4% Part Time, 4% Temporary, and 11% Contract. Highlights an 74% In-person, 11% Hybrid, and 15% Remote job distribution.
Senior Data Scientist - Marketing & Customer Analytics

Senior Data Scientist - Marketing & Customer Analytics

PNC Bank

Wilmington, DE • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


PNC Bank rating

7.7

Company rating: 7.7 out of 10

Based on 340 frontline employees who took The Breakroom Quiz

80th of 149 rated banks


Job description

Position OverviewAt PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company's success. As a Senior Data Scientist within PNC's Data, Modeling & Analytics organization specifically within our Marketing & Customer Analytics group, you will be based in Pittsburgh, PA, Tysons Corner or Vienna, VA or Wilmington, DE.
The Senior Data Scientist - Marketing Valuations will play a critical role in accelerating profitable growth by developing, scaling, and applying valuation analytics and statistical models to enable decisionmaking across marketing strategies.
This role focuses on translating customer, offer, and channel economics into actionable valuation frameworks that inform prioritization, optimization, and investment decisions.
The ideal candidate combines expertise in statistical modeling and advanced analytics with business acumen to deliver analytical solutions for Marketing Valuations.
Key Responsibilities:
Valuation model development & Financial Forecasting: Design and develop valuation and forecasting models such as: Net Present Values, Customer Lifetime Value and Offer Economics to guide marketing budget optimization and investment decisions.
Apply advanced statistical and causal modeling to quantify incremental impact, uncertainty and trade-offs.
Strategic Decision Support: Analyze large datasets to understand customer behavior and translate insights into clear business cases with measurable outcomes.
End-to-End Analytical Ownership: Own the full analytical lifecycle, from problem framing and data exploration to model development and validation.
Cross-functional collaboration: Partners with marketing strategy, finance, and data teams to drive adoption of valuation outputs, advise on their application, and present findings clearly to senior executives to support strategic decisions.
Preferred Skills and Experience:
Advanced degree in a quantitative field (e.g., mathematics, statistics, economics etc.) is preferred.
Progressive experience in data science, advanced analytics, or quantitative modeling, preferably in financial services or marketing analytics.
Demonstrated expertise in marketing valuation concepts, including customer lifetime value, incremental or causal value and offer or channel economics.
Intermediate proficiency in Python and SQL. Knowledge of cloud platforms and big data technologies (Spark, Hadoop).
Excellent communication skills with the ability to explain complex approaches to non-technical and executive stakeholders.
Strong attention to detail.PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals.PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position.Job Description
  • Leads the implementation of analytical projects that leverage vast amounts of structured and unstructured data to extract actionable business insights.
  • Directs the data gathering, data processing and data mining of large and complex datasets.
  • Leads the development of algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
  • Leads analytical experiments in a methodical manner to find opportunities for product and process optimization. Presents business insights to management using visualization technologies and data storytelling.
  • Partners with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:

  • Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
  • Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.
Qualifications

Successful candidates must demonstrate appropriate knowledge, skills, and abilities for a role. Listed below are skills, competencies, work experience, education, and required certifications/licensures needed to be successful in this position.

Preferred SkillsAnalytical Thinking, Competitive Advantages, Data Analytics, Data Mining, Data Science, Machine Learning (ML)CompetenciesData Architecture, Data Mining, Disruptive Innovation, Information Capture, Machine Learning, Modeling: Data, Process, Events, Objects, Prototyping, Query and Database Access ToolsWork ExperienceRoles at this level typically require a university / college degree, with 5+ years of industry-relevant experience. Specific certifications are often required. In lieu of a degree, a comparable combination of education, job specific certification(s), and experience (including military service) may be considered.EducationMastersCertificationsNo Required Certification(s)LicensesNo Required License(s)Pay TransparencyBase Salary: $100,100.00 - $185,900.00Salaries may vary based on geographic location, market data and on individual skills, experience, and education. This role is incentive eligible with the payment based upon company, business and/or individual performance.Application WindowGenerally, this opening is expected to be posted for two business days from 04/09/2026, although it may be longer with business discretion.BenefitsPNC offers a comprehensive range of benefits to help meet your needs now and in the future. Depending on your eligibility, options for full-time employees include: medical/prescription drug coverage (with a Health Savings Account feature), dental and vision options; employee and spouse/child life insurance; short and long-term disability protection; 401(k) with PNC match, pension and stock purchase plans; dependent care reimbursement account; back-up child/elder care; adoption, surrogacy, and doula reimbursement; educational assistance, including select programs fully paid; a robust wellness program with financial incentives.In addition, PNC generally provides the following paid time off, depending on your eligibility: maternity and/or parental leave; up to 11 paid holidays each year; 9 occasional absence days each year, unless otherwise required by law; between 15 to 25 vacation days each year, depending on career level; and years of service.

To learn more about these and other programs, including benefits for full time and part-time employees, visitpncthrive.com.

Disability Accommodations Statement

If an accommodation is required to participate in the application process, please contact us via email at AccommodationRequest@pnc.com. Please include "accommodation request" in the subject line title and be sure to include your name, the job ID, and your preferred method of contact in the body of the email. Emails not related to accommodation requests will not receive responses. Applicants may also call 877-968-7762 and say "Workday" for accommodation assistance. All information provided will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.


At PNC we foster an inclusive and accessible workplace. We provide reasonable accommodations to employment applicants and qualified individuals with a disability who need an accommodation to perform the essential functions of their positions.

Equal Employment Opportunity (EEO)


PNC provides equal employment opportunity to qualified persons regardless of race, color, sex, religion, national origin, age, sexual orientation, gender identity, disability, veteran status, or other categories protected by law.

This position is subject to the requirements of Section 19 of the Federal Deposit Insurance Act (FDIA) and, for any registered role, the Secure and Fair Enforcement for Mortgage Licensing Act of 2008 (SAFE Act) and/or the Financial Industry Regulatory Authority (FINRA), which prohibit the hiring of individuals with certain criminal history.

California Residents

Refer to the California Consumer Privacy Act Privacy Notice to gain understanding of how PNC may use or disclose your personal information in our hiring practices.


What PNC Bank employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom