We are seeking a highly experienced Data Scientist with deep expertise in telecom services, AI/ML, and data management to drive the delivery of data products, intelligent cognitive use cases, and Autonomous Network solutions for Communication Service Providers (CSPs). The role requires strong technical skills, telco domain knowledge, and the ability to engage with both executive and technical stakeholders in a services environment.

If you have:

Strong knowledge of telecom network data (OSS/BSS, CDRs, performance, fault, CX data).Expertise in Python, SQL, PySpark, TensorFlow/PyTorch, Scikit-learn.Hands-on experience with Vertex AI, Red Hat OpenShift AI, Kubeflow, and Kubernetes.Awareness of Generative AI, LLM-Ops, and Agentic AI applications in telecom.MLOps: MLflow, Kubeflow Pipelines, ArgoCD, GitOps.Strong communication skills to engage with executive stakeholders and technical teams.Bachelor’s/Master’s in Computer Science, Statistics, Data Science, Mathematics, or related field.

15+ years total experience, including 10+ years in telecom domain and 5+ years in AI/ML & cloud technologies.

 

It would be nice if you also had:

Ab-intio data management platformFamiliarity with network automation, service assurance, and intent-based networking.Exposure to standards: 3GPP, TM ForumPre-sales experience: RFPs, solution demos, customer workshops.Knowledge of Data Mesh, Data Fabric, and MLOps frameworks.Experience with Snowflake, Databricks, Kafka, Flink, Airflow.Visualization: Tableau, Power BI, Grafana.

 

#LI-Hybrid
 

Design, develop, and deliver AI/ML use cases for Autonomous Networks (AN).Build and manage cognitive data products and frameworks supporting large-scale telecom deployments of AI/ML use cases.Research and implement new ML techniques to improve existing systems and solve novel problems.Partner with CSP customers to translate requirements into scalable data-driven solutions.Implement ML pipelines using platforms such as Vertex AI, Red Hat OpenShift AI, and Kubeflow.Manage end-to-end data lifecycle: ingestion, feature engineering, training, deployment, and monitoring.Establish frameworks for monitoring model performance, detecting drift, and automating retraining.Ensure solutions align with 3GPP, TM Forum , and CSP frameworks.Support pre-sales efforts through RFP responses, PoCs, and customer demos.Contribute to knowledge assets, accelerators, and reusable delivery frameworks for AI/ML use cases.Provides direction and sets expectations for creating new business opportunities, and evaluates new technology solutions. Acts as a senior delivery subject matter expert for data science and ML for Autonomous Networks