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Sr. Manager, Data Science & Applied AI

Sr. Manager, Data Science & Applied AI

451 Discovery Comm. IndiaBegumpet, Telangana, India
1 day ago
Job description

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 bringing our characters to life, the bringing them to your living rooms and the 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 Senior 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.

2. 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.
  • 4. 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., SageMaker, 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.
  • 5. 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, TensorFlow, PyTorch, 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 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.

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    Manager Data Science • Begumpet, Telangana, India

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