Analyst - Machine Learning Marketing NG at MTN Nigeria

Description:

• Collect, analyze, interpret, and summarize data in preparation for generation of statistical and analytical reports and provide intelligence that supports decision-making 
• Proactively analyze data to answer key questions from stakeholders or out of shelf curiosity with an eye for what drives business performance, investigating and communicating areas for improvement in efficiency and productivity 
• Support CVM commercial team to identify opportunity base for campaign creation. 
• Utilize specified statistical software to analyze and interpret research data, as appropriate to the individual position. 
• Understand customer demographics, usage, and behavior to drive decision making on retention and value creation.  
• Provide support to campaign segmentation analyst as required. 
• Contribute and participate in campaign idea generation meetings and cross functional Customer Lifecycle Management meeting as required 
• Data mining and statistical modelling for various machine learning use-cases. 
• Searching and selecting appropriate data sets before performing data collection and data modelling. 
• Training and retraining ML systems and models as needed. 
• Work closely with data engineers, business analyst, statisticians and subject matter experts to drive deep analysis and uncover useful insights. 
• Identifying differences in data distribution that could affect model performance in real-world situations. 
• Visualizing data for deeper insights. 
• Analysing the use cases of ML algorithms and ranking them by their success probability. 
• Understanding when your findings can be applied to business decisions. 
• Verifying data quality and/or ensuring it via data cleaning. 
• Explain and infer the results of various algorithmic approaches and evaluating their performance. 
• Design systems, alerts, and dashboards to monitor machine learning workflows. 
• Documenting machine learning processes. 
• Ensuring that ML algorithms generate accurate CVM recommendations. 

Education:

• First degree in Mathematics, Statistics, Computer Science, Engineering or other related disciplines. 
• Fluent in English 

Experience:

3 - 7 years’ experience which includes

• 1 – 2 years’ experience in AI/ML analyst roles. 
• Understanding of big data technologies. 
• Advanced proficiency with Python, SQL and PySpark. 
• Experience in aggregating & transforming data, exploring & manipulating data, creating training & inference pipelines, building & validating models. 
• Extensive knowledge of ML frameworks, libraries, data structures, data modelling, and software architecture 
• Certification in machine learning, data engineering, data science or related fields will be an added advantage. 
• Strong analytical, problem-solving and teamwork skills. 
• Good oral & written communications skills. 
• Experience working in a medium organization. 
• Solid understanding of predictive analysis: predictive modelling, machine learning and data mining. 
• Good understanding of customer data analysis, propensity modelling and segmentation techniques; excellent understanding of data manipulation and interrogation techniques.