Senior Data Scientist -( IIT ) IRC292274

Job description

**Description** Job Description **About The Role** We are seeking a highly skilled Data Scientist to design, develop, and deploy AI/ML models that power data mapping, anomaly detection, and reconciliation automation within large-scale projects. This role combines strong data science expertise with practical engineering skills to build intelligent systems that improve Telecom Platform, reduce manual effort, and ensure high-quality outcomes. The ideal candidate has hands-on experience with machine learning model development, data engineering, and cloud-based AI/ML workflows, along with exposure to the telecom domain. Key Responsibilities AI/ML Model Development Design, develop, and deploy ML models for automated data mapping, anomaly detection, reconciliation, fraud detection, and churn prediction. Conduct data profiling, feature engineering, and exploratory analysis to improve accuracy and performance. Select appropriate algorithms (supervised, unsupervised, reinforcement learning) based on business needs. Automation & Integration Build end-to-end ML pipelines for data ingestion, preprocessing, training, validation, and deployment. Integrate models into Telecom Platform and Automation frameworks, enabling seamless execution in production. Monitor model performance, implement retraining strategies, and optimize for scalability and reliability. Collaboration & Delivery Work with cross-functional teams (engineering, architecture, QA, business SMEs) to align AI solutions with Telecom Platform and enterprise requirements. Translate business requirements into clear technical specifications, user stories, and acceptance criteria. Contribute to platform innovation by adopting latest AI/ML advancements in anomaly detection and reconciliation automation. Knowledge Sharing & Mentorship Document AI models, frameworks, and best practices for reusability. Mentor junior engineers/data scientists, fostering a collaborative and learning-oriented environment. What You Bring Experience: 5 to 8 years of experience in developing and deploying machine learning models in production. Hands-on experience in Classification, anomaly detection, or reconciliation automation is highly preferred. Proven track record of delivering AI/ML projects from ideation to production deployment.. Technical Skills: Strong knowledge of ML algorithms and techniques (supervised, unsupervised, anomaly detection, NLP, and deep learning). Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch). Experience with data pipelines, ETL/ELT, Delta Lake, and data lakehouse architectures. Cloud-based ML experience (Azure Data Factory, Azure Databricks, AWS Sagemaker, GCP AI/ML). Skilled in PySpark for large-scale data processing. Familiarity with containerization (Docker, Kubernetes) for scalable deployment. Strong grounding in data reconciliation frameworks and automation techniques. Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Building & deploying model using Python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture. Excellent problem-solving and analytical skills. Communication and collaboration skills. Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field. Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. **Requirements** About the Role We are seeking a highly skilled Data Scientist to design, develop, and deploy AI/ML models that power data mapping, anomaly detection, and reconciliation automation within large-scale projects. This role combines strong data science expertise with practical engineering skills to build intelligent systems that improve Telecom Platform, reduce manual effort, and ensure high-quality outcomes. The ideal candidate has hands-on experience with machine learning model development, data engineering, and cloud-based AI/ML workflows, along with exposure to the telecom domain. Key Responsibilities AI/ML Model Development Design, develop, and deploy ML models for automated data mapping, anomaly detection, reconciliation, fraud detection, and churn prediction. Conduct data profiling, feature engineering, and exploratory analysis to improve accuracy and performance. Select appropriate algorithms (supervised, unsupervised, reinforcement learning) based on business needs. Automation & Integration Build end-to-end ML pipelines for data ingestion, preprocessing, training, validation, and deployment. Integrate models into Telecom Platform and Automation frameworks, enabling seamless execution in production. Monitor model performance, implement retraining strategies, and optimize for scalability and reliability. Collaboration & Delivery Work with cross-functional teams (engineering, architecture, QA, business SMEs) to align AI solutions with Telecom Platform and enterprise requirements. Translate business requirements into clear technical specifications, user stories, and acceptance criteria. Contribute to platform innovation by adopting latest AI/ML advancements in anomaly detection and reconciliation automation. Knowledge Sharing & Mentorship Document AI models, frameworks, and best practices for reusability. Mentor junior engineers/data scientists, fostering a collaborative and learning-oriented environment. What You Bring Experience: 5 to 8 years of experience in developing and deployin