Data Scientist & Machine Learning Engineer

Introduction

We are seeking a highly skilled Machine Learning Engineer with expertise in the telecommunications domain to join our team. The ideal candidate will have hands-on experience in developing machine learning models for pre-paid modelling, ISP sales simulations, and customer chain predictions. This role involves designing, developing, and optimizing predictive models that drive business insights and strategic decision-making.

Duties & Responsibilities • Develop and implement machine learning models for pre-paid subscriber behavior forecasting. • Design and enhance ISP sales simulation models to optimize sales strategies. • Build customer chain prediction models to improve retention, churn management, and lifetime value assessments. • Work closely with data scientists, analysts, and engineers to refine datasets and improve model accuracy. • Optimize ML solutions for real-time analytics and scalability in a telecom environment. • Ensure data integrity, compliance, and security while handling telecom datasets.

Desired Experience & Qualification • Bachelor’s degree in computer science, Engineering, Mathematics, or a related field. • 3–5 years of experience in machine learning and predictive modeling, preferably in the telecom sector. • Proven expertise in working with telecom-related datasets, including prepaid customer behavior, sales trends, and churn prediction. • Proficiency in ML frameworks such as TensorFlow, PyTorch, Scikit-learn. • Strong experience in Python, R, or Scala for ML model development. • Knowledge of telecom-specific KPIs, subscriber segmentation, and revenue optimization models. Familiarity with big data technologies like Spark, Hadoop, and cloud ML solutions (AWS/GCP/Azure)