Comcast brings together the best in media and technology We drive innovation to create the world s best entertainment and online experiences As a Fortune 50 leader we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines We are at the forefront of change and move at an amazing pace thanks to our remarkable people who bring cutting-edge products and services to life for millions of customers every day If you share in our passion for teamwork our vision to revolutionize industries and our goal to lead the future in media and technology we want you to quick-forward your career at Comcast Job Summary Responsible for contributing to the development and deployment of machine learning algorithms Evaluates accuracy and functionality of machine learning algorithms as a part of a larger team Contributes to translating application requirements into machine learning problem statements Analyzes and evaluates solutions both internally generated as well as third party supplied Contributes to developing ways to use machine learning to solve problems and discover new products working on a portion of the problem and collaborating with more senior researchers as needed Works with moderate guidance in own area of knowledge Core Responsibilities About the Role We are seeking an experienced Data Scientist to join our growing Operational Intelligence team You will play a key role in building intelligent systems that help reduce alert noise detect anomalies correlate events and proactively surface operational insights across our large-scale streaming infrastructure You ll work at the intersection of machine learning observability and IT operations collaborating closely with Platform Engineers SREs Incident Managers Operators and Developers to integrate smart detection and decision logic directly into our operational workflows This role offers a unique opportunity to push the boundaries of AI ML in large-scale operations We welcome curious minds who want to stay ahead of the curve bring innovative ideas to life and improve the reliability of streaming infrastructure that powers millions of users globally What You ll Do Design and tune machine learning models for event correlation anomaly detection alert scoring and root cause inference Engineer features to enrich alerts using service relationships business context change history and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts metrics traces and logs Use Python SQL and time-series query languages e g PromQL to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations automate workflows and ensure production readiness Contribute to the development of self-healing automation diagnostics and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A B testing offline validation and live performance monitoring of ML models Build and share clear dashboards visualizations and reporting views to support SREs engineers and leadership Participate in incident postmortems providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML rule-based systems to support dynamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs POVs and exploration of emerging AI ML tools and strategies Demonstrate a proactive solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor s or Master s degree in Computer Science Data Science Machine Learning Statistics or a related field 3 years of experience building and deploying ML solutions in production environments 2 years working with AIOps observability or real-time operations data Strong coding skills in Python including pandas NumPy Scikit-learn PyTorch or TensorFlow Experience working with SQL time-series query languages e g PromQL and data transformation in pandas or Spark Familiarity with LLMs prompt engineering fundamentals or embedding-based retrieval e g sentence-transformers vector DBs Strong grasp of modern ML techniques including gradient boosting XGBoost LightGBM autoencoders clustering e g HDBSCAN and anomaly detection Experience managing structured unstructured data and building features from logs alerts metrics and traces Familiarity with real-time event processing using tools like Kafka Kinesis or Flink Strong understanding of model evaluation techniques including precision recall trade-offs ROC AUC calibration Comfortable working with relational PostgreSQL NoSQL MongoDB and time-series InfluxDB Prometheus databases Ability to collaborate effectively with SREs platform teams and participate in Agile DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git Confluence JIRA collaborative agile environments Nice to Have Experience building or contributing to the AIOps platform e g Moogsoft BigPanda Datadog Aisera Dynatrace BMC etc Experience working in streaming media OTT platforms or large-scale consumer services Exposure to Infrastructure as Code Terraform Pulumi and modern cloud-native tooling Working experience with Conviva Touchstream Harmonic New Relic Prometheus event- based alerting tools Hands-on experience with LLMs in operational contexts e g classification of alert text log summarization retrieval-augmented generation Familiarity with vector databases e g FAISS Pinecone Weaviate and embeddings-based search for observability data Experience using MLflow SageMaker or Airflow for ML workflow orchestration Knowledge of LangChain Haystack RAG pipelines or prompt templating libraries Exposure to MLOps practices e g model monitoring drift detection explainability tools like SHAP or LIME Experience with containerized model deployment using Docker or Kubernetes Use of JAX Hugging Face Transformers or LLaMA Claude Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS GCP especially for distributed training storage or batch inferencing Contributions to open-source ML or DevOps communities or participation in AIOps research benchmarking efforts Certifications in cloud architecture ML engineering or data science specialization Comcast is proud to be an equal opportunity workplace We will consider all qualified applicants for employment without regard to race color religion age sex sexual orientation gender identity national origin disability veteran status genetic information or any other basis protected by applicable law Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work Most sales positions are eligible for a Commission under the terms of an applicable plan while most non-sales positions are eligible for a Bonus Additionally Comcast provides best-in-class Benefits to eligible employees We believe that benefits should connect you to the support you need when it matters most and should help you care for those who matter most That s why we provide an array of options expert guidance and always-on tools that are personalized to meet the needs of your reality - to help support you physically financially and emotionally through the big milestones and in your everyday life Please visit the compensation and benefits summary on our careers site for more details Education Bachelor s Degree While possessing the stated degree is preferred Comcast also may consider applicants who hold some combination of coursework and experience or who have extensive related professional experience Relevant Work Experience 2-5 Years

📌 Data Scientist 2 (Tamil Nadu)
🏢 Comcast
📍 Tamil Nadu