Job Role : Data ScientistExp : 4+ YearsLocation: Singapore ( onsite)Qualifications:Experience with ML models is a must Proven experience as a Data Scientist, Data Analyst, or similar role, specifically in the Telecom domain or with/for a Telecom company involved in OPEX analysis. Strong knowledge of statistical analysis, data modeling, machine learning, and predictive analytics techniques. Proficiency in programming languages such as Python, R, or Scala, and familiarity with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow). Experience with data visualization tools like Tableau, Power BI, or matplotlib. Familiarity with big data technologies (e.g., Hadoop, Spark) and SQL for data extraction and manipulation. Solid understanding of telecom industry concepts, including mobile networks, tower infrastructure, OPEX components, and cost drivers. Excellent problem-solving skills and the ability to think analytically and critically. Strong communication and interpersonal skills, with the ability to effectively collaborate with diverse stakeholders. Proven track record of delivering data-driven insights and recommendations to drive business value.Skills :Analyze and model operational expenditure (OPEX) associated with operating mobile towers for our telecom clients. Work with a large set of disparate cost data sources and would have to build visulations of Opex over time Leverage ML models to forecast cost (feature engineering) and implement anomaly detection Develop and implement advanced data analytics methodologies to extract meaningful insights from large and complex datasets related to OPEX. Collaborate with cross-functional teams, including telecom operators, finance, operations, and engineering, to gather requirements and understand the business context. Design and develop predictive models and forecasting algorithms to support OPEX analysis and cost optimization initiatives.Identify patterns, trends, and anomalies in OPEX data to generate actionable insights and recommendations for process improvement and cost reduction. Utilize statistical and machine learning techniques to build predictive models for OPEX forecasting, considering factors like tower location, maintenance, energy consumption, and network utilization. Develop data visualizations and reports to communicate findings and insights effectively to stakeholders. Stay up-to-date with the latest industry trends, technologies, and best practices in data science and telecommunications to drive innovation and improve OPEX analysis capabilities.
Job Role : Data ScientistExp : 4+ YearsLocation: Singapore ( onsite)Qualifications:Experience with ML models is a must Proven experience as a Data Scientist, Data Analyst, or similar role, specifically in the Telecom domain or with/for a Telecom company involved in OPEX analysis. Strong knowledge of statistical analysis, data modeling, machine learning, and predictive analytics techniques. Proficiency in programming languages such as Python, R, or Scala, and familiarity with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow). Experience with data visualization tools like Tableau, Power BI, or matplotlib. Familiarity with big data technologies (e.g., Hadoop, Spark) and SQL for data extraction and manipulation. Solid understanding of telecom industry concepts, including mobile networks, tower infrastructure, OPEX components, and cost drivers. Excellent problem-solving skills and the ability to think analytically and critically. Strong communication and interpersonal skills, with the ability to effectively collaborate with diverse stakeholders. Proven track record of delivering data-driven insights and recommendations to drive business value.Skills :Analyze and model operational expenditure (OPEX) associated with operating mobile towers for our telecom clients. Work with a large set of disparate cost data sources and would have to build visulations of Opex over time Leverage ML models to forecast cost (feature engineering) and implement anomaly detection Develop and implement advanced data analytics methodologies to extract meaningful insights from large and complex datasets related to OPEX. Collaborate with cross-functional teams, including telecom operators, finance, operations, and engineering, to gather requirements and understand the business context. Design and develop predictive models and forecasting algorithms to support OPEX analysis and cost optimization initiatives.Identify patterns, trends, and anomalies in OPEX data to generate actionable insights and recommendations for process improvement and cost reduction. Utilize statistical and machine learning techniques to build predictive models for OPEX forecasting, considering factors like tower location, maintenance, energy consumption, and network utilization. Develop data visualizations and reports to communicate findings and insights effectively to stakeholders. Stay up-to-date with the latest industry trends, technologies, and best practices in data science and telecommunications to drive innovation and improve OPEX analysis capabilities.
