
Leading company in the entertainment industry
Principal, Data Scientist
必須スキル
Machine Learning
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 Principal, Ad Tech Data Scientist reports to the Sr Director, CALS and leads 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 strategic influence, the Principal 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 Principal partners with engineering, product, and sales to embed machine learning into the core of WBD’s advertising workflows.
Your Role Accountabilities:Advanced Modeling & AI Strategy
- Define the vision and roadmap for machine learning, optimization, and AI systems that drive forecasting accuracy, yield optimization, and audience targeting.
- Develop novel models in time-series forecasting, reinforcement learning, optimization, and causal inference tailored for advertising use cases.
Experimentation & Innovation –
- Design and oversee experimentation frameworks, A/B testing, and measurement systems to evaluate model impact.
- Advance audience intelligence, personalization, and cross-platform reach/frequency models.
- Explore emerging AI/ML approaches to maintain WBD’s competitive edge in advertising innovation.
Modernization & Optimization of Data Platforms The Principal drives the evolution of legacy data systems into modular, cost-optimized platforms. They lead rationalization to eliminate redundancy, embed observability and lineage, and establish automation practices that improve performance, reliability, and efficiency.
Leadership & Strategic Partnership:
- Act as a hands-on technical expert and advisor, translating data science into actionable strategies for sales, product, and operations stakeholders.
- Provide guidance and share best practices within the team
- Engage externally with AI/ML communities, vendors, and partners to influence industry direction and accelerate adoption of next-generation methods.
Qualifications & Experience
·Education: Advanced degree in Computer Science, Statistics, Applied Mathematics, Operations Research, or related technical discipline required. Advanced specialization in optimization, machine learning, or large-scale AI systems strongly preferred.
·Data Science Leadership: 12+ years of applied data science experience, with proven success in deploying ML models into production at enterprise scale (including MIPS-scale or equivalent high-throughput systems).
·Advanced Modeling Expertise: Deep knowledge of statistical optimization, stochastic modeling, reinforcement learning, deep learning, and causal inference applied to advertising, media, or high-scale transactional domains.
·Scalable ML Systems: Demonstrated experience building cloud-native ML/AI pipelines (AWS Sage Maker, Bedrock, Databricks, Tensor Flow, Py Torch, Spark ML) with focus on performance, cost efficiency, and scalability.
·Optimization & Yield: Expertise in statistical optimization and decision science techniques for forecasting, yield management, and pricing algorithms in ad-tech or related industries.
·Experimentation & Measurement: Strong background in A/B testing, multi-armed bandits, attribution modeling, and quantifying model-driven business impact.
·Operational Excellence: Skilled in MLOps, CI/CD for ML, model governance, bias detection, and observability frameworks.
·Communication & Influence: Proven ability to articulate advanced data science concepts to C-level executives and influence product, sales, and engineering stakeholders.
·Industry Engagement: Active participation in ML/AI communities, publications, patents, or open-source contributions highly valued
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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Warner Bros. Discoveryについて

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+
従業員数
New York City
本社所在地
$20B
企業価値
レビュー
10件のレビュー
3.5
10件のレビュー
ワークライフバランス
2.8
報酬
4.0
企業文化
4.2
キャリア
3.0
経営陣
2.5
65%
知人への推奨率
良い点
Good benefits and compensation
Supportive team and great colleagues
Innovative and creative projects
改善点
Poor management and leadership issues
Work-life balance challenges
High pressure and workload
給与レンジ
4件のデータ
L3
L4
L5
L3 · Data Scientist I
0件のレポート
$124,580
年収総額
基本給
-
ストック
-
ボーナス
-
$105,893
$143,267
面接レビュー
レビュー9件
難易度
2.1
/ 5
期間
21-35週間
内定率
22%
体験
ポジティブ 33%
普通 67%
ネガティブ 0%
面接プロセス
1
Application Review
2
Phone Screen
3
Technical Interview
4
Final Interview
5
Offer Decision
よくある質問
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Past Experience
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