Data Scientist

We are seeking a skilled Data Scientist with 7+ years of experience, specializing in the telecom industry. This role involves applying data science, advanced analytics, and machine learning techniques to uncover insights that drive strategic decisions, enhance customer experience, and improve network operations. You will work with cross-functional teams to support key telecom-specific projects, including customer churn prediction, network optimization, and predictive maintenance. Key Responsibilities Perform exploratory data analysis on large telecom datasets, including customer behavior, network traffic, and service usage, to identify trends and patterns. Develop, validate, and deploy predictive models using machine learning techniques to address telecom challenges, such as customer churn prediction, fraud detection, and network demand forecasting. Clean, preprocess, and engineer telecom data to create robust datasets for model training and improve model accuracy. Design and conduct A/B tests and experiments to assess the effectiveness of new telecom features or campaigns. Use statistical models and algorithms to optimize network performance, improve call quality, and minimize downtime. Create dashboards and reports to communicate insights and KPIs to both technical and non-technical stakeholders. Work closely with product, marketing, and network engineering teams to translate business needs into data science solutions and convey complex insights. Required Skills & Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. 3–5 years of hands-on experience as a data scientist, preferably within the telecom industry. Technical Skills: Strong proficiency in Python and/or R for statistical analysis, data manipulation, and model development. Proficiency with machine learning libraries and tools such as Scikit-Learn, TensorFlow, PyTorch, and XGBoost. Advanced SQL skills and experience with telecom data, such as call detail records (CDR) and network logs. Familiarity with big data tools like Apache Spark, Hadoop, or Hive for large-scale data processing. Proficiency in visualization tools (e.g., Tableau, Power BI) and libraries (e.g., Matplotlib, Seaborn) to convey findings clearly. Understanding of telecom-specific data, including customer usage metrics, network KPIs, and regulatory requirements. Strong problem-solving and analytical abilities to develop models that address business-specific challenges in telecom. Ability to communicate complex data insights to stakeholders at all levels and collaborate effectively across functions. Preferred Qualifications Advanced Machine Learning & NLP: Experience with deep learning, natural language processing (NLP), or anomaly detection for telecom applications like sentiment analysis or network monitoring. Telecom Protocols & Standards: Familiarity with telecom standards, including LTE, 5G, and telecom-specific protocols. Certifications: Relevant certifications like AWS Certified Machine Learning, Google Professional Machine Learning Engineer, or telecom-related certifications. #J-18808-Ljbffr