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Data Science Research Assistant Remote Jobs in Delaware

We clear the way by pairing exceptional Executive Assistants with our driven clients, providing ... Role Overview The Data Science Intern will help us to understand the performance of Executive ...

Data Analyst

Lewes, DE ยท On-site +1

... ranging from market research and trend analysis to performance tracking and forecasting. Your ... Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related field.

AI Adoption Specialist

Wilmington, DE ยท On-site +1

$35 - $45/hr

At least 1 year of experience in data science, analytics, automation, or AIrelated work. Desired ... remote candidates will be considered. This role requires access to U.S. export-controlled ...

Senior AI Engineer

Wilmington, DE ยท On-site +1

$101K - $139K/yr

This is a remote role and will report directly to the Head of Data Science & AI. The role ... R&D, Supply Chain, and Sales. You'lljoin a highly collaborative team that values speed and quality ...

Senior Tax Research Specialist

Dover, DE ยท Remote

$69K - $69K/yr

Senior Tax Research Specialist United States Monday to Friday 8:00 am to 5:00 pm Remote We are ... Eventually lead or assist other leaders on team projects, as needed * Provide support for the ...

Threat Analysis and Research: Dive deep into terabytes of SaaS Application data to identify new ... Collaborate with security researchers and data scientists to define new threat detection strategies ...

New

Oversee scientific advisory mechanisms, including advisory boards, special topic working groups, and research summits. * Representing Agilent within the global scientific community and promote ...

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Data Science Research Assistant Remote information

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

To thrive as a Data Science Research Assistant (Remote), a solid background in statistics, programming (Python or R), and data analysis, often supported by relevant coursework or a degree, is essential. Familiarity with data visualization tools (e.g., Tableau), databases (SQL), and platforms like Jupyter Notebook, as well as experience with machine learning libraries, is typically required. Strong problem-solving abilities, attention to detail, self-motivation, and effective remote communication skills make candidates stand out. These competencies are crucial for managing complex data tasks, collaborating with team members virtually, and delivering reliable analytical insights.

What are common challenges faced by remote Data Science Research Assistants, and how can they be addressed?

Remote Data Science Research Assistants often encounter challenges such as maintaining clear communication with team members, managing time across different projects, and accessing necessary datasets or computing resources. Overcoming these hurdles typically involves leveraging collaboration tools like Slack or Zoom for regular check-ins, setting clear expectations with supervisors on deliverables, and ensuring secure, remote access to data and software. Proactively seeking feedback and participating in virtual team meetings can help foster a sense of connection and keep projects on track.

What is the difference between Data Science Research Assistant Remote vs Data Analyst Remote?

AspectData Science Research Assistant RemoteData Analyst Remote
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's or Master's in Data Analysis, Statistics, or related field
Work EnvironmentRemote research projects, academic or research institutionsRemote data interpretation and reporting for various industries
Employer & Industry UsageUniversities, research labs, tech companiesBusiness, finance, healthcare, marketing

While both roles involve working with data remotely, Data Science Research Assistants focus on research projects, often in academic or research settings, requiring a strong foundation in data science and statistics. Data Analysts typically analyze and interpret data for business insights across various industries. The roles share similar credentials but differ in their primary focus and work environment.

What are Data Science Research Assistants (Remote)?

A Data Science Research Assistant (Remote) is a professional who supports data scientists and research teams by collecting, cleaning, analyzing, and visualizing data, often from a remote location. Their responsibilities may include assisting with experiment design, performing statistical analyses, preparing datasets, creating reports, and helping to develop or test machine learning models. Working remotely, they utilize collaboration tools and cloud platforms to work efficiently with distributed teams. This role is ideal for individuals with strong analytical skills, programming knowledge (such as Python or R), and an interest in research and data-driven problem solving.
What are popular job titles related to Data Science Research Assistant Remote jobs in Delaware? For Data Science Research Assistant Remote jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Data Science Research Assistant Remote jobs in Delaware look for? The top searched job categories for Data Science Research Assistant Remote jobs in Delaware are:
What cities in Delaware are hiring for Data Science Research Assistant Remote jobs? Cities in Delaware with the most Data Science Research Assistant Remote job openings:

VP of Data Science (Remote)

Forbes Advisor

Wilmington, DE โ€ข On-site, Remote

Full-time

Posted 5 days ago

New


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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