{"id":1575899,"url":"https://alion.io/job/pressroom-principal-data-scientist-2","title":"Principal Data Scientist","company":{"id":21042,"name":"Warner Bros. Discovery","domain":"wbd.com","url":"https://alion.io/company/pressroom","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":75,"open_postings":19,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-02T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":26000,"max_usd":46000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":14,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"OCR","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-07-14T00:00:00Z","employer_posted_date":"2026-07-14","last_verified_at":"2026-10-02T14:41:15Z","board_verified":true,"closed_at":null,"days_open":81,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":81},"description":"Welcome to Warner Bros. Discovery… the stuff dreams are made of.\nWho We Are…\nWhen 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…\nFrom 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.\nAs a Principal Data Scientist, you will play a pivotal role in architecting, developing, and deploying high-impact machine learning and data science solutions across Warner Bros. Discovery’s global businesses. This role is ideal for a seasoned technical leader with 14-16 years of total experience, including 10-12 years of deep, hands-on experience in applied data science, machine learning, and statistical modeling. You will translate complex business problems into scalable analytical solutions-leveraging predictive modeling, optimization, experimentation, NLP, computer vision, and modern ML engineering practices. You will lead end-to-end development of ML models, champion scientific rigor, and ensure robust operationalization through modern MLOps practices. Experience in the Media & Entertainment sector-content, streaming, audience behavior, ad intelligence, or metadata systems-is a significant plus. This is a high-impact role requiring strong technical expertise, business acumen, problem-solving skills, and the ability to guide cross functional partners across Product, Engineering, Technology, and Business domains.\n1. Core Data Science & Machine Learning Expertise\nDesign, build, and scale advanced machine learning models across predictive analytics, NLP, CV, forecasting, optimization, and recommender systems.\nApply strong statistical foundations-hypothesis testing, probability modeling, causal inference, and experiment design-to solve complex business problems.\nDevelop interpretable and explainable ML models, ensuring scientific rigor, reproducibility, and operational robustness.\nConduct feature engineering, model selection, hyperparameter tuning, and validation using modern ML frameworks.\nTranslate ambiguous problems into structured analytic approaches with measurable impact.\n2. ML Engineering & MLOps Execution\nBuild production-grade ML pipelines integrating with WBD’s data ecosystem (Snowflake, AWS, GCP, Databricks).\nImplement CI/CD, model monitoring, drift detection, alerting, and model performance governance.\nContribute to the design of feature stores, experimentation platforms, and ML observability frameworks.\nWork closely with data engineering and platform teams to ensure scalable, reliable model deployment.\n3. Applied Data Science Delivery for High-Value Business Problems Lead delivery of ML solutions for domains such as:\nContent performance and ratings prediction\nAudience segmentation, churn and lifetime value modeling\nSearch ranking, discovery, and personalization systems\nMetadata enrichment and content understanding using NLP & CV\nOperational forecasting and automation Convert analytical outcomes into actionable insights-delivering high-ROI recommendations to product and business stakeholders.\n4. Stakeholder Partnership & Communication\nPartner with senior leaders across Streaming, Technology, Product, Content, and Marketing.\nPresent complex modeling results clearly to non-technical audiences, influencing business decisions with data-driven insights.\nShape and guide analytical roadmaps aligned to enterprise priorities.\n5. Leadership, Collaboration & Mentoring\nMentor data scientists and ML engineers, elevating scientific rigor and best practices across the team.\nLead project teams in experimentation, modeling, evaluation, and productionization.\nPromote knowledge sharing, documentation standards, and internal communities of practice.\nChampion responsible AI, model governance, and ethical data usage across engagements.\nQualifications & Experiences:\nMaster’s degree (or Ph.D. preferred) in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related fields.\n14-16 years of total experience, with 10-12 years in Data Science, ML, and advanced analytics.\nStrong hands-on expertise in:Predictive modeling, optimization, deep learning, NLP, and CV\nPython, SQL, PyTorch/TensorFlow, Scikit-learn, ML frameworks\nML Ops, model deployment, monitoring, and observability\nStatistical modeling, experiment design, Bayesian methods\nCloud platforms (AWS/GCP/Snowflake)\n\nDemonstrated track record of delivering business impact through ML solutions in large-scale environments.\nStrong communication skills with demonstrable ability to influence cross-functional teams.\nPreferred:\nExperience in Media & Entertainment, streaming, digital advertising, metadata, or audience intelligence.\nHands-on exposure to foundation models, LLMs, embeddings, or generative AI.\nExperience with video intelligence, OCR/CV pipelines, or content metadata engines.\nPublications, patents, or conference-level contributions in ML/AI.\nHow We Get Things Done…\nThis 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.\nChampioning Inclusion at WBD\nWarner 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.","description_format":"text","description_chars":6457,"description_truncated":false,"requirements":{"experience_years_min":14,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Cybersecurity","Media & Entertainment","Standards & Industry Bodies"],"lifecycle":[{"event":"open","at":"2026-10-01T10:03:06Z"}],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.396,"p_room":0.28,"age_days":80,"expected_fill_days":30,"reasons":["conf:15","stale_co","win:tail","crowd:brand"],"computed_at":"2026-10-02T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/pressroom-principal-data-scientist-2","json_url":"https://alion.io/job/pressroom-principal-data-scientist-2.json","meta":{"generated_at":"2026-10-03T00:46:30Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":488,"day_limit":5000,"remaining_today":4512,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}