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Remote Data Science Startup Jobs in Delaware (NOW HIRING)

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 ...

Native

Advertising Sales Executive

Wilmington, DE · On-site +1

$71K - $90K/yr

Remote US native has been building for 10 years, but we're still very much a startup: fast-moving ... Log interactions and updates accurately in the CRM system to ensure data integrity and smooth ...

Quora

$139K - $168K/yr

Take end-to-end ownership of Machine Learning systems -- from prototyping, data pipelines and ... D. in Computer Science, Engineering or a related technical field * Strong understanding of ...

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Remote Data Science Startup information

What are some unique challenges of working as a data scientist at a remote startup, and how can I prepare for them?

Working as a data scientist at a remote startup often involves navigating ambiguous project requirements, rapidly shifting priorities, and a high degree of autonomy. You may find yourself balancing multiple roles, such as data engineering and analysis, especially when the team is small. Strong communication skills are essential for collaborating effectively across time zones and ensuring alignment with product and business goals. Preparing by developing self-management habits, proactively seeking feedback, and becoming comfortable with remote collaboration tools will help you thrive in this dynamic environment.

What is a remote data science startup?

A Remote Data Science Startup is a company focused on developing data-driven solutions, analytics, or products, with a team that primarily works remotely rather than from a central office. These startups leverage data science techniques such as machine learning, statistical analysis, and big data processing to solve business problems or create innovative products. Employees collaborate using digital tools and platforms, allowing for flexible work arrangements and access to a global talent pool. Remote data science startups often serve various industries, including healthcare, finance, e-commerce, and technology.

What are the key skills and qualifications needed to thrive at a remote data science startup, and why are they important?

To thrive at a remote data science startup, you need strong analytical skills, proficiency in statistics, and experience with programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with tools such as Jupyter Notebook, SQL databases, cloud platforms (e.g., AWS, GCP), and version control systems like Git is typically required. Exceptional self-motivation, communication, and collaboration skills are crucial to excel in a remote and fast-paced startup environment. These competencies enable you to deliver actionable insights, adapt to rapid changes, and collaborate effectively across distributed teams.
What are the most commonly searched types of Data Science Startup jobs in Delaware? The most popular types of Data Science Startup jobs in Delaware are:
What are popular job titles related to Remote Data Science Startup jobs in Delaware? For Remote Data Science Startup jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Remote Data Science Startup jobs in Delaware look for? The top searched job categories for Remote Data Science Startup jobs in Delaware are:
What cities in Delaware are hiring for Remote Data Science Startup jobs? Cities in Delaware with the most Remote Data Science Startup job openings:
Remote Data Science Startup jobs near you
Infographic showing various Remote Data Science Startup job openings in Delaware as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Re-posted 5 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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