Company Overview :

Deutsche Telekom Digital Labs is the digital innovation hub of Deutsche Telekom, one of the worlds leading integrated telecommunications companies. Based in Gurugram, the organization focuses on building scalable digital products and platforms that serve millions of customers across Europe. By leveraging cutting-edge technology and agile methodologies, the team drives the digital transformation of telecommunications services, ensuring seamless connectivity and superior user experiences in a rapidly evolving global market.

Role Overview :

As a Data Science Engineer, you will be at the forefront of developing intelligent solutions that optimize network performance and enhance customer engagement. You will work closely with cross-functional engineering teams, product managers, and data architects to translate complex business requirements into robust machine learning models. Your work will directly influence the efficiency of our digital platforms, ensuring that data-driven insights are integrated into the core of our telecommunications infrastructure to improve service delivery and operational outcomes.

Key Responsibilities :

- Design and deploy scalable machine learning models to solve complex telecommunications challenges, directly impacting system performance and customer satisfaction.

- Engineer end-to-end data pipelines using Hadoop to process large-scale datasets, ensuring high availability and data integrity for downstream analytics.

- Implement advanced deep learning architectures using frameworks like TensorFlow and PyTorch to automate predictive maintenance and anomaly detection.

- Integrate state-of-the-art Natural Language Processing models from Hugging Face to improve customer support automation and sentiment analysis.

- Collaborate with software engineering teams to transition research-grade models into production environments, ensuring seamless integration with existing digital platforms.

- Monitor model performance and iterate on algorithms to maintain high accuracy and relevance in a dynamic, high-traffic production environment.

Required Skillset :

- Demonstrated proficiency in Python for data manipulation, statistical analysis, and building production-ready machine learning applications.

- Strong hands-on experience in developing and fine-tuning deep learning models using TensorFlow, PyTorch, and Hugging Face libraries.

- Proven ability to manage and process massive datasets within a Hadoop ecosystem, optimizing queries for performance and scalability.

- Excellent problem-solving skills with the ability to communicate complex technical concepts to non-technical stakeholders effectively.

- A collaborative mindset, comfortable working in a fast-paced, hybrid work environment alongside global teams.

- A Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related quantitative field.

- 4 - 7 years of professional experience in building and deploying data science solutions in a large-scale enterprise environment.