About this role
Company Description
Company Introduction – T-Systems ICT India Pvt. Ltd. T-Systems Information and Communication Technology India Private Limited (T-Systems ICT India Pvt. Ltd.) is a certified Great Place To Work®, proudly recognized for its strong people-first culture and commitment to employee excellence. As a wholly owned subsidiary of T-Systems International GmbH, T-Systems India operates out of Pune and Bangalore, with a dynamic team of over 4,200 professionals delivering high-value IT services to group customers worldwide. T-Systems India plays a key role in this global vision by delivering integrated, end-to-end IT solutions and sector-specific software to drive transformation across industries, including automotive, manufacturing, logistics, transportation, healthcare, and the public sector. For over 25 years, T-Systems International GmbH has been at the forefront of digital innovation, driving progress and fostering digital optimism. As a leading European IT services provider and a proud part of Deutsche Telekom, T-Systems delivers transformative digitalization projects backed by deep expertise in consulting, cloud, AI, cybersecurity, and connectivity. With a global workforce of 26,000 employees across 26 countries, we set industry benchmarks in efficiency, sovereignty, security, and reliability—empowering organizations to unlock their full digital potential. With annual revenues exceeding EUR 4.0 billion (2024), T-Systems stands as one of Europe’s foremost digital transformation partners, committed to shaping the future of enterprise technology.
Job Description
Key Responsibilities Analyze large volumes of structured and unstructured data to extract meaningful insights Build validate and deploy machine learning models for predictive analytics and automation Design and implement machine learning pipelines for structured and unstructured data Work closely with business stakeholders and cross functional teams including data engineers analysts to translate problems into data driven solutions Build dashboards and data visualizations to communicate findings effectively Conduct testing hypothesis validation and experiment tracking Optimize model performance and ensure scalability and maintainability in production environments Document methodology workflow and results clearly for future reference and compliance Continuously monitor model performance and retrain based on data drift and feedback loops Required Skills Tools Category Skills Tools Programming Python pandas scikit learn NumPy matplotlib seaborn R SQL Machine Learning Supervised unsupervised learning time series forecasting clustering NLP deep learning optional Statistical Analysis Hypothesis testing regression models Bayesian inference multivariate analysis Data Engineering Data preprocessing cleaning feature engineering large dataset handling Big Data Tools Spark Hadoop Hive Model Deployment MLflow Docker Kubernetes for advanced roles Visualization Power BI Tableau Plotly Matplotlib Seaborn Databases SQL NoSQL MongoDB Cassandra cloud native databases BigQuery Redshift Snowflake Cloud Platforms AWS SageMaker Redshift GCP Vertex AI BigQuery Azure ML Studio Data Lake Version Control Git GitHub GitLab Collaboration Experience working with Agile teams using tools like Jira Confluence Slack
Additional Information
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