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Remote Data Jobs in Delaware (NOW HIRING)

Winaxis LLC

Data Analyst

Lewes, DE · On-site +1

As a Data Analyst at Winaxis LLC, you will be responsible for extracting, transforming, and presenting data in a meaningful way to support various projects and initiatives. This role is essential in ...

Heirloom Cloud

DoD SkillBridge Intern- REMOTE

Wilmington, DE · Remote

$14.50 - $19.50/hr

SkillBridge Intern- REMOTE Heirloom Cloud Corporation recruits remote interns to be part of a fast ... Data Analytics * Search Engine Optimization * Digital Marketing * Social Media Management * Sales ...

Agilent

Advanced Data Analyst

Wilmington, DE · On-site +1

$74K - $139K/yr

Join us at the forefront of our data transformation journey, where your expertise will help shape the next generation of analytics platforms and drive business value through actionable insights. We ...

Heirloom

DoD SkillBridge Intern- REMOTE

Wilmington, DE · On-site +1

$14.50 - $19.50/hr

SkillBridge Intern- REMOTE Heirloom Cloud Corporation recruits remote interns to be part of a fast ... Data Analytics * Search Engine Optimization * Digital Marketing * Social Media Management * Sales ...

Trella Health

S. locations in a remote capacity. Reports to: Director, Product As a Product Manager at Trella, you will: * Own product strategy, roadmap, and execution for a clinical data domain spanning the full ...

ABB

Data Center COE Project Management Leader

DE · Remote

$119K - $190K/yr

Remote in the US This role is contributing to the ELSE Data Center Services Center of Excellence in the United States. Core Responsibilities: * Shape and execute projectdelivery strategy aligned with ...

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All JobsData JobsRemote Data JobsRemote Data Jobs in Delaware

Remote Data information

See Delaware salary details

$46K

$165.2K

$243.7K

How much do remote data jobs pay per year?

As of Jul 31, 2026, the average yearly pay for remote data in Delaware is $165,160.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,600.00 and $170,100.00 per year, depending on experience, location, and employer.

What are some common challenges faced when working as a Remote Data Analyst, and how can they be addressed?

Remote Data Analysts often face challenges such as maintaining effective communication with team members, managing access to secure data, and staying aligned with project goals across different time zones. These can be addressed by leveraging collaboration tools like Slack or Microsoft Teams, following strict data security protocols, and participating in regular virtual meetings to ensure everyone is on the same page. Proactive communication and strong organizational skills are key to thriving in a remote data role.

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

AspectRemote DataRemote Data Analyst
Required CredentialsBachelor's in Data Science, Computer Science, or related field; knowledge of databases and data toolsBachelor's in Data Science, Statistics, or related; proficiency in data analysis tools like Excel, SQL, and visualization software
Work EnvironmentRemote, often independent, with collaboration via online platformsRemote, involves analyzing data sets, creating reports, and communicating findings
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceBusiness, marketing, finance, and tech sectors

Remote Data generally refers to roles focused on managing and processing data, while Remote Data Analyst emphasizes analyzing data to generate insights. Both roles often require similar educational backgrounds and work remotely, but Data Analysts typically focus more on interpreting data and creating reports for decision-making.

How can I make 2000 a week working from home?

Remote data roles such as data analyst or data scientist can offer high earning potential, with experienced professionals earning $2,000 or more weekly through project-based work, consulting, or full-time employment. Building skills in data analysis tools, programming languages, and obtaining relevant certifications can help increase earning capacity, especially when working independently or in specialized niches.

Are there real remote data entry jobs?

Yes, remote data entry jobs are available and involve inputting information into digital systems from home. These roles typically require basic computer skills, attention to detail, and sometimes familiarity with spreadsheet or database software. Legitimate positions are often posted on reputable job boards and do not require upfront fees.

How to make $1000 a week remotely?

Remote data roles such as data analyst or data scientist can generate $1000 or more weekly with experience, strong analytical skills, and proficiency in tools like Excel, SQL, or Python. Achieving this income often involves freelance projects, contract work, or full-time positions with high pay rates, and may require certifications or specialized knowledge in data management and analysis.

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

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a background in data science or a related field. Familiarity with data analysis tools such as Python, R, SQL, and platforms like Tableau or Power BI, along with relevant certifications, is typically required. Excellent self-motivation, time management, and communication skills help you stand out in a remote environment. These capabilities are crucial for delivering accurate insights, collaborating effectively from a distance, and meeting business objectives efficiently.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

What are remote data jobs?

Remote data jobs are positions that involve collecting, analyzing, managing, or interpreting data while working from a location outside the traditional office environment. These roles can include data analysts, data scientists, data entry specialists, and database administrators, among others. Remote data professionals use online tools and platforms to access and process data, collaborate with teams, and deliver insights or reports. This flexible work arrangement allows individuals to contribute to data-driven projects from anywhere with an internet connection.
What are the most commonly searched types of Data jobs in Delaware? The most popular types of Data jobs in Delaware are:
What are popular job titles related to Remote Data jobs in Delaware? For Remote Data jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Remote Data jobs in Delaware look for? The top searched job categories for Remote Data jobs in Delaware are:
What cities in Delaware are hiring for Remote Data jobs? Cities in Delaware with the most Remote Data job openings:
Remote Data jobs near you
Infographic showing various Remote Data job openings in Delaware as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $165,160 per year, or $79.4 per hour.

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Posted 24 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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