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Analyst - Data Scientist at MTN Nigeria

MTN NigeriaLagos, Nigeria Data and Artificial Intelligence
Full Time

MTN Nigeria is part of the MTN Group, Africa\'s leading cellular telecommunications company. On May 16, 2001, MTN became the first GSM network to make a call following the globally lauded Nigerian GSM auction conducted by the Nigerian Communications Commission earlier in the year. Thereafter the company launched full commercial operations beginning with Lagos, Abuja and Port Harcourt. MTN paid $285m for one of four GSM licenses in Nigeria in January 2001. To date, in excess of US$1.8 billion has been invested building mobile telecommunications infrastructure in Nigeria. Since launch in August 2001, MTN has steadily deployed its services across Nigeria. It now provides services in 223 cities and towns, more than 10,000 villages and communities and a growing number of highways across the country, spanning the 36 states of the Nigeria and the Federal Capital Territory, Abuja. Many of these villages and communities are being connected to the world of telecommunications for the first time ever. The company\'s digital microwave transmission backbone, the 3,400 Kilometre Y\'elloBahn was commissioned by President Olusegun Obasanjo in January 2003 and is reputed to be the most extensive digital microwave transmission infrastructure in all of Africa. The Y\'elloBahn has significantly helped to enhance call quality on MTN network.

Mission:

  • Apply strong expertise in machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services.
  • Collaborate with translators to define technical problem statements and hypotheses to test; develop efficient and accurate analytical models that mimic business decisions.
  • Build high-quality data pipelines that drive analytic solutions.

Description:

  • Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
  • Design, create, test, and implement complex models and algorithms that drive analytical solutions throughout the organization.
  • Conduct advanced statistical and other analysis to provide actionable insights, identify trends, and measure performance.
  • Collaborate with translators and understand business problems to implement scalable and sustainable solutions.
  • Coordinate with MIS, digital specialists, and data engineers to deliver holistic analytical solutions.
  • Support translators in communicating the design, functioning, and output of the analytical models and solutions developed.
  • Utilize specified statistical software to analyze and interpret research data, as appropriate to the individual position.
  • Ensure timely analysis and testing for regular maintenance of solutions over time.

Education:

  • First degree in mathematics, statistics, computer science, engineering, or other related disciplines.
  • Certification in machine learning, data engineering, data science, or related fields will be an added advantage.
  • Fluent in English

Experience:

3–7 years’ experience, with experience working with others.

  • 1–3 years’ experience in a statistical and/or data science/business intelligence role
  • Understanding of big data technologies.
  • Experience with programming is required, including R, Python, SQL, and PySpark.
  • Experience working with large data sets, simulation/optimization, and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.) is a plus.
  • Solid understanding of predictive analysis: predictive modeling, machine learning, and data mining
  • Experience in aggregating and transforming data, exploring and manipulating data, creating training and inference pipelines, and building and validating models
  • Experience working with basic visualization tools such as Tableau, Qlik, etc.
  • Strong analytical, problem-solving, and teamwork skills
  • Excellent written and verbal communication skills, along with a strong desire to work in cross-functional teams.
  • Openness to working in agile environments with multiple stakeholders
  • Good oral and written communication skills

Method of Application

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