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채용Warner Bros. Discovery

Sr. Staff, Data Science & Applied AI

Warner Bros. Discovery

Sr. Staff, Data Science & Applied AI

Warner Bros. Discovery

Hyderabad, Telangāna, India

·

On-site

·

Full-time

·

4w ago

필수 스킬

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:

As the Sr. Manager, Data Science & Applied AI, you will play a pivotal role in driving the implementation of impactful AI/ML solutions across the enterprise. You will be responsible for managing a high-performing team of data scientists and machine learning engineers, delivering solutions that enhance operational efficiency, audience engagement, and decision intelligence in the Media & Entertainment ecosystem. This is a strategic and hands-on leadership position focused on developing cutting-edge ML/AI products—ranging from predictive models and recommender systems to generative AI and computer vision use cases—while ensuring robust production deployment and adoption.

1.End-to-End AI Solution Delivery & Technical Oversight

  • Lead the full lifecycle of AI/ML project delivery: from problem formulation and hypothesis generation to data acquisition, feature engineering, model development, deployment, and continuous optimization.

  • Design and review advanced statistical models, machine learning algorithms, and deep learning architectures for tasks such as customer segmentation, forecasting, personalization, natural language processing, image/video analysis, and generative content creation.

  • Ensure solutions are built for scale, performance, and robustness using modern engineering and MLOps practices—e.g., CI/CD pipelines for models, monitoring dashboards, automated retraining loops.

  • Guide model explainability, fairness, and compliance practices in line with Responsible AI guidelines.

Strategic Team Leadership & Capability Building:

  • Manage, mentor, and grow a high-performing team of data scientists and ML engineers by defining clear roles, growth paths, and technical competencies.

  • Lead regular code reviews, model design sessions, and innovation sprints to ensure rigor, reusability, and excellence.

  • Foster a culture of curiosity, continuous learning, and business alignment, encouraging contributions to internal AI knowledge bases, innovation forums, and external conferences.

  • Define and implement team KPIs that measure both technical quality and business impact.

3.Business Problem Translation & Stakeholder Management

  • Act as a bridge between business challenges and AI solutions by deeply understanding domain pain points and framing them into solvable data science problems.

  • Partner with business stakeholders across functions (e.g., revenue, audience insights, ad sales, content strategy) to identify AI use cases with high ROI.

  • Develop compelling narratives and visualizations to communicate results and recommendations to non-technical stakeholders, including senior executives.

  • Regularly present outcomes, risks, and learnings to steering committees, ensuring transparency and strategic alignment.

AI Productization & Operationalization:

  • Ensure that models are not just proof-of-concepts but are integrated into production systems with real-time or batch inference pipelines.

  • Design scalable APIs, model versioning, and deployment artifacts using best-in-class tooling (e.g., Sage Maker, MLflow, Vertex AI, or Kubeflow).

  • Work with DevOps and platform teams to standardize model deployment workflows, automate drift detection, and reduce time-to-market for ML products.

  • Maintain a post-deployment monitoring framework to track model health, user feedback, and business performance indicators.

  1. Governance, Risk Management & Ethical AI
  • Partner with Legal, Compliance, and Risk functions to implement guardrails for ethical AI use, especially in sensitive areas like user profiling or content moderation.

  • Establish frameworks for model documentation, reproducibility, audit trails, and change control.

  • Stay abreast of global AI regulations and proactively align team practices with internal and external compliance requirements.

Qualifications & Experiences:

  • Master’s degree (or higher) in Computer Science, Data Science, AI/ML, Statistics, or a related field.

  • 12–14 years of overall experience in AI/ML or data science, including 7–9 years in managerial or tech-lead roles.

  • Demonstrated experience in developing and deploying machine learning models in production environments.

  • Proficiency in Python and frameworks like scikit-learn, Tensor Flow, Py Torch, or similar.

  • Strong knowledge of cloud platforms (preferably AWS or GCP) and containerization tools (Docker, Kubernetes).

  • Experience in working with structured and unstructured data, including video, image, and text.

  • Solid understanding of data engineering concepts and collaboration with DevOps and engineering teams.

  • Excellent communication and stakeholder engagement skills.

  • Prior exposure to Media & Entertainment use cases is a plus

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 소개

Warner Bros. Discovery

Warner 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+

직원 수

New York City

본사 위치

$20B

기업 가치

리뷰

3.8

3개 리뷰

워라밸

2.5

보상

2.0

문화

3.0

커리어

3.5

경영진

2.0

35%

친구에게 추천

장점

Good technical experience and projects

Strong performance recognition

Team connections and networking

단점

Poor work-life balance

Unreliable offer management

Limited career progression

연봉 정보

2개 데이터

L3

L4

L5

L3 · Data Scientist I

0개 리포트

$124,580

총 연봉

기본급

-

주식

-

보너스

-

$105,893

$143,267

면접 경험

9개 면접

난이도

2.1

/ 5

소요 기간

21-35주

합격률

22%

경험

긍정 33%

보통 67%

부정 0%

면접 과정

1

Application Review

2

Phone Screen

3

Technical Interview

4

Final Interview

5

Offer Decision

자주 나오는 질문

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience