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Remote Data Science Student Jobs in Delaware (NOW HIRING)

Trella Health

You'll partner closely with data science, engineering, and GTM teams to ship AI-powered analytics ... S. locations in a remote capacity. Reports to: Director, Product As a Product Manager at Trella ...

Morson Talent

AI Adoption Specialist

Wilmington, DE · On-site +1

$35 - $45/hr

... data science, analytics, automation, or AI. Eligibility Requirements The preferred work location for this role is at the GEH Headquarters in Wilmington, NC; but highly qualified (US based) remote ...

The Chemours Company

Senior AI Engineer

Wilmington, DE · On-site +1

$101K - $139K/yr

This is a remote role and will report directly to the Head of Data Science & AI. The role willidentify,solution, build, and launch GenAI products & traditional apps in all areas of the company ...

Siemens

Remote Perks: * Potential for full-time offers after university graduation and completion of the ... Analyze engagement and program data to measure pilot success, track adoption metrics, and provide ...

Siemens

Remote Perks: * Potential for full-time offers after university graduation and completion of the ... Analyze engagement and program data to measure pilot success, track adoption metrics, and provide ...

Siemens

Remote Perks: * Potential for full-time offers after university graduation and completion of the ... Analyze engagement and program data to measure pilot success, track adoption metrics, and provide ...

Siemens

Remote Perks: * Potential for full-time offers after university graduation and completion of the ... Analyze engagement and program data to measure pilot success, track adoption metrics, and provide ...

Siemens

Remote Perks: * Potential for full-time offers after university graduation and completion of the ... Analyze engagement and program data to measure pilot success, track adoption metrics, and provide ...

Siemens

Remote Perks: * Potential for full-time offers after university graduation and completion of the ... Analyze engagement and program data to measure pilot success, track adoption metrics, and provide ...

Siemens

Remote Perks: * Potential for full-time offers after university graduation and completion of the ... Analyze engagement and program data to measure pilot success, track adoption metrics, and provide ...

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All JobsData Science Student JobsRemote Data Science Student JobsRemote Data Science Student Jobs in Delaware

Remote Data Science Student information

What is the difference between Remote Data Science Student vs Remote Data Analyst?

AspectRemote Data Science StudentRemote Data Analyst
Required CredentialsEnrolled in or recently completed data science courses, certificationsDegree in statistics, mathematics, or related field; some certifications
Work EnvironmentLearning-focused, internship or entry-level projects, mentorshipAnalyzing data, creating reports, supporting decision-making
Employer & Industry UsageEducational institutions, internships, entry-level roles in tech, finance, healthcareBusinesses across industries, performing routine data analysis tasks

The main difference is that a Remote Data Science Student is typically in training or early learning stages, focusing on gaining skills through coursework and internships. In contrast, a Remote Data Analyst is usually engaged in applying existing skills to analyze data and generate insights for organizations. Both roles are entry-level but differ in experience, responsibilities, and focus areas.

What are remote data science students?

Remote data science students are individuals who study data science through online programs or courses, rather than attending classes in person. They learn key concepts such as statistics, machine learning, and programming using digital resources and remote instruction. This flexible approach allows students to access high-quality education from anywhere, often at their own pace. Remote data science students may participate in virtual classes, complete assignments online, and collaborate with peers and instructors through digital platforms.

How do Remote Data Science Students typically collaborate and communicate with peers and instructors to enhance their learning experience?

Remote Data Science Students often engage with peers and instructors through online platforms such as discussion forums, video calls, and collaborative coding environments. Regular participation in virtual study groups, project teams, and mentorship sessions can help students stay motivated and deepen their understanding of complex topics. Proactively reaching out for feedback, sharing progress, and contributing to group projects are key ways to build valuable connections and learn industry-relevant teamwork skills, even in a remote setting.

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

To thrive as a Remote Data Science Student, you need a solid grounding in statistics, programming (Python or R), and data analysis, often supported by a relevant undergraduate degree or coursework. Familiarity with tools like Jupyter Notebooks, SQL, Git, and data visualization software is essential, along with experience using online learning platforms. Strong time management, self-motivation, and effective communication skills help you stay on track and engage with peers and instructors remotely. Mastering these skills ensures you can independently acquire knowledge, complete projects, and collaborate effectively in a virtual learning environment.
What are popular job titles related to Remote Data Science Student jobs in Delaware? For Remote Data Science Student jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Remote Data Science Student jobs in Delaware look for? The top searched job categories for Remote Data Science Student jobs in Delaware are:
What cities in Delaware are hiring for Remote Data Science Student jobs? Cities in Delaware with the most Remote Data Science Student job openings:
Remote Data Science Student jobs near you
Infographic showing various Remote Data Science Student job openings in Delaware as of July 2026, with employment types broken down into 5% Internship, 76% Full Time, 14% Part Time, and 5% Temporary. Highlights an 100% Remote job distribution.

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Posted 26 days ago

Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:
  • Commercial Data Science: Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. You'll shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes.
  • Marketing Science & Decision Science: Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. You'll help define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta.
  • Production Data Science: Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products rather than one-off analyses. You'll champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle.
  • Leadership & Stakeholder Management: Lead and develop a growing team of Data Scientists while building trusted relationships across the business. You'll translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and help establish Data Science as a trusted driver of business strategy and commercial growth.
  • Innovation & Industry Leadership: Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science. You'll evaluate emerging technologies, bring new ideas into the organisation and help ensure our Data Science capability remains commercially relevant and technically leading.

Qualifications:
  • Experience leading commercial Data Science, Marketing Science or Decision Science teams.
  • Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling.
  • Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding.
  • Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams.
  • Strong understanding of SQL, Python and modern machine learning frameworks.
  • Experience working with Google Ads, Meta or other major advertising platforms.
  • Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences.
  • Experience building and developing high-performing Data Science teams.
  • Strong commercial judgement, balancing technical excellence with measurable business impact.
  • A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.

Nice to Have
  • Experience within affiliate marketing, digital publishing or lead-generation businesses.
  • Experience working in financial services, insurance or regulated industries.
  • Experience working directly with Google or Meta Data Science teams.
  • Experience with attribution modelling and marketing measurement.
  • Experience building optimisation algorithms for DSPs or advertising platforms.
  • Experience with causal inference, experimentation frameworks or incrementality testing.
  • Experience forecasting marketing or commercial performance.
  • Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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