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Remote Decision Scientist Jobs in Delaware (NOW HIRING)

Dlapiper

Data Scientist

Wilmington, DE · On-site +1

... decision trees, neural networks, data mining techniques, etc. * Experience with most or all of the ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

CSC Corptax

Senior Tax Technology Consultant

Dover, DE · Remote

$81K - $100K/yr

Senior Tax Technology Consultant Remote-Americas Monday-Friday 8:00 am to 5:00 pm CSC Corptax is ... Apply emerging AI capabilities to accelerate analysis, documentation, and decision support-while ...

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Remote Decision Scientist information

What is a remote decision scientist?

A Remote Decision Scientist is a professional who analyzes data and uses statistical models to help organizations make informed decisions, all while working from a remote location. They combine expertise in data science, business analytics, and decision theory to solve complex problems and guide strategic direction. Their work often involves gathering and interpreting large data sets, running simulations, and providing actionable recommendations to stakeholders. Remote Decision Scientists leverage communication tools and collaborative platforms to work effectively with teams across different locations.

What skills and qualifications are needed to be a remote decision scientist?

To thrive as a Remote Decision Scientist, you need strong analytical skills, proficiency in statistics, and a background in data science or a related field, often supported by a relevant degree. Familiarity with programming languages like Python or R, experience with data visualization tools, and knowledge of machine learning platforms are typically required. Clear communication, problem-solving abilities, and self-motivation are essential soft skills for collaborating remotely and conveying complex insights. These skills ensure effective data-driven decision-making, impactful recommendations, and seamless remote teamwork.

How does a remote decision scientist collaborate with cross-functional teams?

Remote Decision Scientists frequently collaborate with product managers, engineers, and business leaders through virtual meetings, shared documentation, and collaborative data platforms. Effective communication is key, as they must clearly explain complex analytical findings and recommendations to both technical and non-technical stakeholders. Tools like Slack, Zoom, and cloud-based analytics environments help bridge the distance, ensuring that decision-making is data-driven and aligned with organizational goals. Regular check-ins and transparent progress updates help maintain strong team integration and project momentum.

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

AspectRemote Decision ScientistRemote Data Analyst
Required CredentialsAdvanced degree in data science, statistics, or related field; strong analytical skillsBachelor's degree in data analysis, statistics, or related field; proficiency in data tools
Work EnvironmentCollaborates with cross-functional teams to develop predictive models and decision frameworksAnalyzes data sets to generate reports and insights for business decisions
Employer & Industry UsageUsed in tech, finance, and e-commerce companies focusing on strategic decision-makingCommon in marketing, retail, and healthcare sectors for operational insights

Remote Decision Scientists focus on building models and frameworks to inform strategic decisions, requiring advanced analytics skills. Remote Data Analysts primarily interpret data to generate reports, often with less emphasis on modeling. Both roles are vital in data-driven industries but differ in complexity and scope.

How much do decision scientists make?

Decision scientists typically earn a median salary between $80,000 and $120,000 annually, depending on experience, location, and industry. Senior roles or those with advanced skills in data analysis, machine learning, and programming can earn higher salaries, often exceeding $150,000.

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What job categories do people searching Remote Decision Scientist jobs in Delaware look for?

The top searched job categories for Remote Decision Scientist jobs in Delaware are:

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Remote Decision Scientist jobs near you

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Re-posted 23 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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