Data Scientist II, Hyderabad

Global Sports Jobs Limited; Phoenix (AZ); On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

A great place to work.

Fast-track growth opportunities.

Career-defining opportunities, curated

A supportive, celebratory environment

Job summary

Discovery is seeking a Data Scientist to lead hands-on modelling and experimentation for global streaming platforms. You will translate complex product questions into data science opportunities, build models, and partner with ML Engineers to productionize validated solutions, impacting identity resolution, audience intelligence, personalization, and advertising effectiveness.

The role sits within SPARK, collaborating with global teams to turn insights into measurable business impact using

Qualifications

• 3–5 years of hands-on data science or ML experience on real-world products or business systems.
• Ability to translate business problems into hypotheses, metrics, and actionable recommendations.
• Knowledge of statistical modeling, ML fundamentals, causal inference, and evaluation.

Responsibilities

• Build and improve models for identity resolution, audience modeling, segmentation, and personalization.
• Design experiments, baselines, success metrics, and promotion criteria with business impact.
• Collaborate with ML Engineers to productionize validated models with monitoring and health checks.
• Work with Product, Engineering, Data Science, Ad Sales, and stakeholders to scope data science solutions.
• Communicate findings and tradeoffs clearly to technical and non-technical audiences.
• Define reusable standards for feature quality, leakage prevention, and production readiness.
• Frame problems with cross-functional teams and translate insights into measurable impact.
• Use Databricks, Snowflake, and AWS as primary platforms; apply modern AI workflows.

Skills

Python

SQL

Experimentation

Statistical modelling

Communication

Collaboration

Education

Master's degree or Ph.D. in CS/Statistics/ML/Data Science/Engineering

Tools

Databricks

Snowflake

AWS

MLflow

Job description

About the Role

As a Data Scientist, the role is a hands-on modelling and experimentation leadership position for WBD's consumer platforms, translating complex product and business questions into measurable data science opportunities. The postholder builds models and evaluation frameworks and partners with Machine Learning Engineering to bring validated solutions into production. The work directly influences identity resolution, audience intelligence, personalization, retention, engagement, advertising effectiveness, and customer experience across WBD's global streaming platforms. The role sits within the SPARK organisation, where Hyderabad-based data science and machine learning teams transform first-party audience signals into capabilities for identity, audience intelligence, advertising, personalization, forecasting, engagement, and retention.

Key Responsibilities

• Build and improve models for probabilistic identity resolution, audience modeling, segmentation, content affinity, genre-preference modeling, forecasting, fraud and abuse detection, promo optimization, personalization, and lifecycle engagement.
• Design experiments, evaluation frameworks, baselines, success metrics, and promotion criteria that measure both model quality and business impact.
• Partner with Machine Learning Engineers to move validated models into scalable production pipelines with clear expectations for reproducibility, monitoring, drift detection, data quality, calibration, and long-term model health.
• Work with Product, Engineering, Data Science, Data Engineering, Ad Sales, and business stakeholders to turn ambiguous opportunities into well-scoped data science solutions.
• Communicate findings, tradeoffs, risks, and recommendations clearly to technical and non-technical audiences.
• Help define reusable standards for feature and label quality, leakage prevention, model evaluation, documentation, experimentation rigor, and production readiness.
• Frame the right problems with Machine Learning Engineering, Product, Data Engineering, Ad Sales, and business teams, and turn insight into measurable product and business impact.
• Use Databricks, Snowflake, and AWS as primary working platforms, alongside modern AI and agentic development workflows where they improve quality, speed, and repeatability.

Required Experience & Qualifications

• 3–5 years of hands-on experience building data science, statistical modeling, or machine learning solutions for real-world products or business systems.
• Strong ability to translate business problems into hypotheses, data science problem statements, success metrics, and actionable recommendations.
• Deep practical knowledge of statistical modeling, machine learning fundamentals, causal inference, experimentation, forecasting, ranking, recommendation, calibration, and model evaluation.
• Strong programming and analytical skills in Python and SQL.
• Hands-on experience with Databricks, Snowflake, AWS, MLflow, notebooks, experiment tracking, or similar data and ML tools.
• Experience partnering with Machine Learning Engineering or platform teams to operationalize models.
• Ability to collaborate effectively with Product, Engineering, Data Engineering, Machine Learning Engineering, Finance, Ad Sales, and business stakeholders in a global environment.
• Excellent communication skills, including the ability to explain technical methods, model tradeoffs, uncertainty, and business implications to varied audiences.

Preferred Skills

• Experience with Spark or large-scale distributed data processing is strongly preferred.
• Master's degree or Ph.D. in Computer Science, Statistics, Machine Learning, Data Science, Engineering, Mathematics, Economics, or a related quantitative field.
• Experience in streaming, media, advertising technology, consumer identity, fraud, recommendations, personalization, forecasting, lifecycle engagement, or audience intelligence.
• Experience with uplift modeling, causal impact analysis, lookalike modeling, clean-room or DCR analysis, graph-based methods, or multi-objective optimization.
• Experience building reusable evaluation frameworks, model quality standards, or scalable data science patterns across teams.
• Working knowledge of Scala as needed.
• Exposure to activation contexts such as personalization systems, Mosaic, FreeWheel, Google Ad Manager, and related audience activation platforms.

Benefits & Perks

• A great place to work.
• Fast-track growth opportunities.
• Career-defining opportunities, thoughtfully curated benefits, and the tools to explore and grow.
• A supportive, celebratory environment where employees can thrive.

About the Company

Discovery is a premier global media and entertainment company with an iconic portfolio of content, brands, and franchises across television, film, streaming, sports, news, and gaming, connecting audiences around the world to the stories, experiences, and moments they love. It brings together iconic entertainment, news, sports, and digital brands including HBO Max, CNN, Discovery+, DC, Warner Bros., Bleacher Report, and Food Network.