Job Description

Mid Data Scientist Engineer, Data Consultant - IT
Johannesburg - GautengAre you ready to be part of a transformational journey that will reshape the digital landscape of Africa? A leading Pan-African telecommunications company is launching a groundbreaking Software Engineering Centre of Excellence (COE); dedicated to building future-focused digital products designed to empower and revolutionize the continent. This is your opportunity to join an innovative team and grow your career at the forefront of technological advancement, as we accelerate towards a brighter, more connected future for Africa.Qualifications:

• Masters or Ph.D. degree in Computer Science, Data Science, Statistics, Engineering, or a related field.

Experience:

• 3+ years of experience in data science, data engineering, or a related field.
• Proven experience leading data projects and managing teams.
• Extensive experience with data analysis, statistical modelling, and machine learning.

Technical Skills:

• Proficiency in programming languages such as Python, R, or Scala.
• Expertise in data processing frameworks like Apache Spark, Hadoop, or similar.
• Strong SQL skills and experience with relational and NoSQL databases.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Advanced knowledge of data visualization tools like Tableau, Power BI, or similar.

Key Responsibilities:

• Data Analysis and Interpretation:

• Analyse and interpret complex datasets to uncover trends, patterns, and actionable insights.
• Develop and implement advanced statistical models and machine learning algorithms to solve business problems.
• Data Engineering:

• Design, develop, and maintain scalable data pipelines and architectures.
• Ensure data quality, integrity, and security across various sources.
• Optimize data storage solutions for efficiency and performance.
• Project Leadership:

• Lead data science and engineering projects from conception to deployment.
• Coordinate with cross-functional teams, including product, engineering, and business stakeholders, to ensure successful project delivery.
• Define project scope, goals, and deliverables that support business objectives.
• Mentorship and Collaboration:

• Mentor and provide guidance to junior data scientists and engineers.
• Foster a collaborative and innovative team environment.
• Communicate complex technical concepts and insights to non-technical stakeholders.
• Research and Development:

• Stay current with the latest advancements in data science, engineering, and machine learning.
• Experiment with new tools, techniques, and technologies to continuously improve data processes and analytics.
• Deployment and Maintenance:

• Deploy and monitor machine learning models in production environments.
• Continuously improve and maintain existing data models and infrastructure.
• Implement best practices for model management and version control.

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