채용
Benefits & Perks
•Learning Budget
•Learning
Required Skills
Machine Learning
Statistical Modeling
Python
TensorFlow
PyTorch
Spark ML
A/B Testing
Experimentation
AWS SageMaker
Databricks
MLOps
Welcome to Warner Bros. Discovery… the stuff dreams are made of.
Who We Are…
When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what’s next…
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.
Your New Role:
The Staff, Data Scientist reports to the Senior Manager, Data Scientist and contributes to the design, development, and deployment of advanced data science models that power WBD’s global advertising ecosystem. This role supports the strategy and execution of ML/AI frameworks for forecasting, optimization, personalization, and audience intelligence. By combining deep technical expertise with project leadership and cross-functional influence, the Staff Data Scientist transforms data into predictive insights that maximize monetization, enhance targeting precision, and enable automation across converged linear and digital platforms.
Acting as a hands-on data scientist, the Staff Data Scientist partners with engineering, product, and sales to embed machine learning into the core of WBD’s advertising workflows.
Your Role Accountabilities:
**Hands-on Modeling &**Solution Delivery
- Build and deploy advanced ML models (forecasting, optimization, personalization).
- Contribute to design of experimentation frameworks and measurement systems.
- Explore emerging ML techniques and assess applicability.
Experimentation & Innovation
-
Design and run A/B tests, validate model impact.
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Advance audience intelligence, personalization, and cross-platform reach/frequency models.
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Explore emerging AI/ML approaches to maintain WBD’s competitive edge in advertising innovation.
Data Platform Collaboration
- Partner with data engineering to optimize pipelines for model performance.
- Contribute to automation and observability improvements.
Mentorship & Cross-Functional Partnership
- Mentor junior data scientists, share best practices.
- Translate technical insights for product and sales teams.
Qualifications & Experience
·Education: Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Operations Research, or related technical discipline required.
·Experience: 8+ years of applied data science experience, including building and deploying machine learning models into production environments.
· Technical Skills:
- Strong proficiency in machine learning techniques such as regression, classification, recommendation systems, and clustering.
- Solid understanding of statistical modeling, optimization methods, and experimentation frameworks (e.g., A/B testing).
- Familiarity with reinforcement learning or causal inference is a plus.
· Tools & Platforms:Hands-on experience with cloud-based ML platforms (AWS SageMaker, Databricks) and frameworks (Tensor Flow, Py Torch, Spark ML).
Working knowledge of MLOps practices, CI/CD pipelines for ML, and model monitoring.
· Domain Knowledge:Exposure to advertising technology, media, or other high-scale transactional domains preferred.
Understanding of forecasting, personalization, and yield optimization techniques is desirable.
· Collaboration & Communication:Ability to work closely with engineering and product teams to integrate models into production workflows.
Skilled at translating technical insights into actionable recommendations for non-technical stakeholders.
· Preferred:Curiosity for emerging AI/ML approaches and commitment to continuous learning.
Contributions to open-source projects or participation in ML/AI communities are a plus but not required.
How We Get Things Done…
This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.
Championing Inclusion at WBD
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.
If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.
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About Warner Bros. Discovery

Warner Bros. Discovery
PublicWarner Bros. Discovery, Inc. (WBD) is an American multinational mass media and entertainment conglomerate headquartered in New York City. It was formed from WarnerMedia's spin-off by AT&T and merger with Discovery, Inc. on April 8, 2022.
10,001+
Employees
New York City
Headquarters
Reviews
3.8
3 reviews
Work Life Balance
2.5
Compensation
2.0
Culture
3.0
Career
3.5
Management
2.0
35%
Recommend to a Friend
Pros
Good technical experience and projects
Strong performance recognition
Team connections and networking
Cons
Poor work-life balance
Unreliable offer management
Limited career progression
Salary Ranges
2 data points
L3
L4
L5
L3 · Data Scientist I
0 reports
$124,580
total / year
Base
-
Stock
-
Bonus
-
$105,893
$143,267
Interview Experience
9 interviews
Difficulty
2.1
/ 5
Duration
21-35 weeks
Offer Rate
22%
Experience
Positive 33%
Neutral 67%
Negative 0%
Interview Process
1
Application Review
2
Phone Screen
3
Technical Interview
4
Final Interview
5
Offer Decision
Common Questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Past Experience
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