Data Scientist

Overview The Data Scientist at Transaction Network Services (TNS) will specialize in leveraging advanced statistical analysis, machine learning, and Generative AI techniques to solve complex international business challenges within the telecommunications industry. This role involves developing, training, and deploying predictive models, enhancing state-of-the-art generative models, and applying cloud engineering principles to create scalable AI solutions. The Data Scientist will work closely with cross-functional teams to extract actionable insights from diverse data sources, contributing to data-driven decision-making and product innovation. Responsibilities

• Utilize expertise in statistical analysis, machine learning, deep learning, and Generative AI techniques to solve complex international business challenges.
• Apply and enhance state-of-the-art generative models for tasks related to telecommunication and industry standardization.
• Develop, train, and deploy predictive models using popular machine learning frameworks and tools.
• Perform data preprocessing, feature engineering, and exploratory data analysis to identify key patterns and trends.
• Collaborate with domain experts and stakeholders to translate business requirements into analytical solutions.
• Design and deploy scalable AI solutions in cloud environments, applying cloud engineering principles.
• Work with software engineers to integrate machine learning models into production systems seamlessly.
• Implement MLOps practices to automate model training, deployment, and monitoring.
• Communicate complex findings to both technical and non-technical stakeholders through clear reports and visualizations.
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• Advanced degree in computer science, machine learning, statistics, or a related field.
• 3 - 7+ years of industry experience in data science roles, with a strong emphasis on machine learning and AI.
• Proficiency in Python and experience with data science frameworks like TensorFlow, PyTorch, and scikit-learn.
• Familiarity with MLOps practices and tools such as Docker, AWS EMR, and AWS SageMaker.
• Strong understanding of data preprocessing techniques, feature engineering, and exploratory data analysis.
• Experience in developing scalable data architectures in a cloud environment.
• Demonstrated ability to work with large data sources, with a focus on data privacy and security.
• Experience working with leadership in different time zones and cultural settings.
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• Excellent written and verbal communication skills, with experience working with globally distributed teams.
• Strong teamwork, creativity, and learning agility, with a passion for data-driven solutions.
• Ability to clearly articulate analytical results and insights to a variety of audiences.
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• Experience developing and launching Generative AI products at scale.
• Deep knowledge of NLP and the latest innovations in Generative AI.
• Experience with big data technologies such as Hadoop, Spark, or Hive.
• Familiarity with software engineering principles and collaborative development practices.
• Experience with test design, decision tree analysis, mathematical programming, and optimization techniques.

Qualifications