Data Scientist at Safaricom Kenya

JOB DESCRIPTION

Reporting to the Lead -Data Scientist, the Data Scientist will develop and run with data-centered projects. In keeping with this overarching aim, the data scientist will be required to outline work requirements, develop, and deliver relevant projects. The role holder will also harness their mastery of Data Science to consult on various aspects of their projects. To be successful in this position, the role holder will use data to ultimately inform and promote the company's expansion.

RESPONSIBILITIES

Key Responsibilities:

• Collaborate with cross-functional teams to understand business needs and identify data analytics opportunities. 
• Collect, clean, and preprocess large datasets from diverse sources, including telecommunications traffic, mobile money transactions, and fibre network performance data.
• Utilize cloud-based analytics tools and platforms to conduct in-depth data analyses, predictive modelling, and data visualization.
• Contribute to the development and deployment of machine learning models to enhance service offerings, optimize network performance, and improve customer satisfaction.
• Monitor and evaluate the effectiveness of data models and analytics solutions, making adjustments as necessary.
• Assist in the integration of data analytics findings into operational processes and strategic planning.
• Stay updated with the latest trends and technologies in data science, telecommunications, and cloud computing.

QUALIFICATIONS

Minimum Qualifications:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. 
• 1-2 years of experience in building data driven solutions with a bias towards machine learning.
• Proficiency in data analytics and machine learning tools (e.g., Python, R, SQL, TensorFlow, PyTorch).
• Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and their data analytics services.
• Strong understanding of data preprocessing, exploratory data analysis, and predictive modelling techniques.
• Familiarity with big data technologies (e.g., Hadoop, Spark) is an advantage.
• Excellent creative problem-solving skills and the ability to work in a fast-paced, dynamic environment.
• Strong communication skills, with the ability to translate complex technical findings into actionable business insights.