Senior Data Scientist – Data Platform Team

Warner Bros. Discovery

Senior Data Scientist developing machine learning models for data-driven solutions at Warner Bros. Discovery.

Posted 7/9/2026full-timeHyderabad • 🇮🇳 IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing, developing, and deploying machine learning models and data science solutions, with a strong focus on end-to-end ML workflows and advanced data science techniques. Proficient in collaborating with cross-functional teams to deliver data-driven solutions while mentoring junior team members.

Highest-signal resume keywords

Machine Learning Model DevelopmentData Science TechniquesPython ProgrammingML Frameworks and LibrariesMLOps Concepts

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData ScienceFeature EngineeringModel TrainingModel ValidationPredictive ModelingNLP TechniquesDeep LearningStatistical AnalysisA/B Testing

Soft Skills

Analytical ThinkingProblem-SolvingCommunication SkillsCross-Functional Collaboration

Tools & Technologies

TensorFlowPyTorchScikit-learnXGBoostKerasSpark ML

Industry Keywords

Data Science Best PracticesScalable ML ArchitecturesProduction ML SystemsLarge-Scale DatasetsDistributed Computing

Tech Stack

Tools & technologies

KerasPythonPyTorchScalaScikit-LearnSparkTensorflow

About the role

Key responsibilities & impact

Design, develop, and deploy machine learning models and data science solutions at scale.
Build ML capabilities using recommendation systems, personalization, predictive modeling, NLP, Generative AI, and Large Language Models (LLMs).
Develop end-to-end ML workflows including data preparation, feature engineering, model training, validation, deployment, monitoring, and optimization.
Apply advanced data science techniques including regression, classification, time series forecasting, causal inference, optimization techniques, and deep learning approaches.
Build and improve scalable ML training and inference pipelines.
Work closely with Data Engineers, ML Engineers, Product Managers, and business teams to deliver data-driven solutions.
Perform experimentation, A/B testing, statistical analysis, and model evaluation to measure model effectiveness.
Research and apply modern ML techniques including Transformers, Deep Learning models, NLP techniques, and AI-based solutions.
Follow and promote data science best practices for model development, evaluation, and deployment.
Mentor junior team members and provide technical guidance when required.

Requirements

What you’ll need

Bachelor’s/Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
5+ years of experience in building data science models and machine learning solutions.
Strong understanding of statistics, machine learning algorithms, probability, and data science fundamentals.
Hands-on experience in developing, deploying, and optimizing ML models in production environments.
Strong programming experience with Python, R, Scala, or similar programming languages.
Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, XGBoost, Keras, and Spark ML.
Experience across the complete ML lifecycle, including feature engineering, training pipelines, model validation, deployment, monitoring, and continuous improvement.
Experience working with large-scale datasets and distributed computing frameworks.
Good understanding of MLOps concepts, scalable ML architectures, and production ML systems.
Strong analytical thinking, problem-solving abilities, communication skills, and cross-functional stakeholder collaboration experience.

Benefits

Comp & perks

Equal opportunity employer
Fast track growth opportunities