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Manager Meta Data Science Jobs in Delaware (NOW HIRING)

OneMain Financial

Manager, Data Science

Wilmington, DE · On-site

Manager, Data Science Location: Wilmington, DE (Hybrid Schedule) OneMain Financial is seeking a Data Science Manager based out of Wilmington, DE, to join our innovative and fast-moving Data Science ...

OneMain Financial

Manager, Data Science

Wilmington, DE · On-site

Manager, Data Science Location: Wilmington, DE (Hybrid) We are seeking a Manager to join our Data Science team in Wilmington, DE. This is an exciting opportunity to develop and manage an integrative ...

OneMain Financial

Manager, Data Science

Wilmington, DE · Hybrid

Manager, Data Science Location: Wilmington, DE (Hybrid) We are seeking a Manager to join our Data Science team in Wilmington, DE. This is an exciting opportunity to develop and manage an integrative ...

CardWorks

Director, Data Science

Wilmington, DE

... external agency management. Position Summary and Role Impact: The Director, Data Science ... Competitive Intelligence, AI Insights & Strategic Analytics is a highly visible leadership role ...

Iff

AI & Data Scientist

Wilmington, DE

... Management Systems (LIMS), SAP, SharePoint and other digital platforms. * Develop and implement data science, machine learning and artificial intelligence solutions that enhance quality processes and ...

ABB

Group Account Manager

DE · Remote

$163K - $261K/yr

As the Group Account Manager, Meta - Data Center Segment, you will have the opportunity to develop, implement, and manage the account strategy that is focused on share of wallet growth, profitability ...

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Manager Meta Data Science information

What does a manager meta data science do?

A Manager of Meta Data Science leads a team of data scientists in developing and implementing advanced analytics, machine learning models, and data-driven strategies for Meta (formerly Facebook). They are responsible for overseeing projects, mentoring team members, collaborating with cross-functional partners, and ensuring that data science solutions align with business goals. This role often requires both technical expertise and strong leadership skills to drive impactful decisions using data. Additionally, they work to improve processes, set research direction, and communicate findings to stakeholders.

How does a manager meta data science typically collaborate with cross-functional teams, and what communication challenges might arise?

A Manager Meta Data Science frequently collaborates with product managers, engineers, data analysts, and business stakeholders to ensure data-driven decision-making aligns with organizational goals. One common challenge is translating complex data science concepts into actionable business insights that are easily understood by non-technical teams. Effective communication and regular alignment meetings are essential to bridge knowledge gaps and ensure everyone is on the same page. Building strong relationships across departments and fostering a culture of transparency can help mitigate misunderstandings and streamline project delivery.

What are the key skills and qualifications needed to thrive as a manager meta data science?

To thrive as a Manager Meta Data Science, you need strong expertise in data science, machine learning, statistical analysis, and a relevant advanced degree, often in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, data visualization tools, and cloud-based platforms, as well as experience with big data frameworks, are typically required. Leadership, strategic thinking, and effective communication are crucial soft skills that enable success in managing teams and collaborating across departments. These skills are important because they ensure the ability to lead complex projects, drive data-driven decision-making, and align analytics goals with organizational objectives.

What are the most commonly searched types of Meta Data Science jobs in Delaware?

The most popular types of Meta Data Science jobs in Delaware are:

What cities in Delaware are hiring for Manager Meta Data Science jobs?

Cities in Delaware with the most Manager Meta Data Science job openings:

Manager Meta Data Science jobs near you

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Re-posted 9 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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