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Overnight Meta Data Scientist Jobs in Delaware (NOW HIRING)

... scientists, digital innovators, program and construction managers and other professionals ... Perform QA/QC of SUE field data and performed by AECOM and its subcontractors. * Troubleshoot ...

... scientists, digital innovators, program and construction managers and other professionals ... Perform QA/QC of SUE field data and performed by AECOM and its subcontractors. * Troubleshoot ...

Overnight Meta Data Scientist information

What is an overnight meta data scientist?

An Overnight Meta Data Scientist is a professional who works primarily during nighttime hours to analyze and interpret large datasets, often utilizing advanced statistical and machine learning techniques. The 'meta' aspect refers to working with metadata—data that provides information about other data—helping organizations optimize data management, enhance searchability, and improve data-driven decision-making. These scientists often monitor automated systems, ensure data pipelines are functioning, and may address urgent issues that arise outside of regular business hours. Their work is critical for organizations that require round-the-clock data processing and analysis, such as global tech companies and online platforms.

What skills and qualifications are needed to thrive as an overnight meta data scientist?

To thrive as an Overnight Meta Data Scientist, you need a strong background in statistics, machine learning, and data analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with programming languages such as Python or R, experience with big data tools like Spark or Hadoop, and proficiency in data visualization platforms are often required. Strong problem-solving skills, attention to detail, and the ability to communicate findings clearly are essential soft skills for this role. These abilities are crucial for extracting actionable insights from complex datasets and supporting data-driven decision-making, even during off-hours when support may be limited.

What are some unique challenges faced by overnight meta data scientists, and how can they be addressed?

Overnight Meta Data Scientists often work during non-standard hours, which can present challenges such as limited real-time collaboration with daytime teams and the need to manage alert fatigue or solo problem-solving. To address these, it's important to establish clear handoff protocols, utilize asynchronous communication tools, and maintain detailed documentation for ongoing projects. Additionally, Overnight Data Scientists often focus on monitoring critical systems or running batch data processes, so developing strong troubleshooting skills and self-reliance is key. Many organizations support these roles with flexible scheduling and remote work options to help maintain work-life balance.

What is the difference between Overnight Meta Data Scientist vs Data Analyst?

AspectOvernight Meta Data ScientistData Analyst
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; knowledge of machine learning and programmingBachelor's in Data Analysis, Statistics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTypically in tech companies or research labs, often with flexible or overnight shiftsUsually in corporate offices, with standard daytime hours
Employer & Industry UsageTech firms, e-commerce, social media platformsFinance, marketing, healthcare, retail

Overnight Meta Data Scientists focus on advanced data modeling, machine learning, and large-scale data analysis, often working overnight shifts in tech environments. Data Analysts primarily handle data collection, cleaning, and reporting during regular hours. While both roles require strong analytical skills, the Meta Data Scientist role emphasizes technical expertise in algorithms and programming, whereas Data Analysts focus on interpreting data for business insights.

What cities in Delaware are hiring for Overnight Meta Data Scientist jobs?

Cities in Delaware with the most Overnight Meta Data Scientist job openings:

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Re-posted 17 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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