Machine Learning Engineer at Data Scientists Network (Data Science Nigeria) - DSN

• We are looking for a Machine Learning Engineer who is passionate about harnessing the power of Azure for end-to-end solutions in machine learning projects.
• This role involves not just developing machine learning models but also managing data, leveraging Azure Synapse for analytics, creating compelling visualizations with Power BI, and utilizing Azure ML Studio for streamlined model development.
• The ideal candidate will be skilled in navigating the Azure ecosystem and be capable of linking various Azure services to create seamless, efficient data pipelines and machine learning workflows.

Key Responsibilities

• Data Management Expertise: Manage and organize data effectively using Azure’s data management tools, ensuring data quality and accessibility.
• Azure Synapse Analytics: Leverage Azure Synapse for complex data analytics tasks, integrating various data sources and applying advanced analytics techniques.
• Power BI Development: Create dynamic and insightful data visualizations and dashboards using Power BI, transforming data into actionable business intelligence.
• Machine Learning with Azure ML Studio: Design, develop, and deploy machine learning models using Azure ML Studio, ensuring models are accurate, efficient, and scalable.
• End-to-End Azure Solutions: Seamlessly integrate various Azure services to create comprehensive end-to-end solutions for machine learning projects.
• Collaboration and Communication: Work closely with cross-functional teams to understand their needs and provide technical solutions. Effectively communicate complex technical concepts to non-technical stakeholders.

Qualifications

• A Bachelor’s degree / HND in Demography, Surveying, Mathematics, Urban Planning, Geography, Geographic Information System, Computer Science, Statistics, Information Management or related field.
• Minimum of 3 / 4 years of progressively responsible experience, implementing, monitoring, evaluation
• Experience with GIS tools and platforms like ARCGIS, QGIS etc.
• Demonstrated analytical skills, and proven experience in developing and facilitating the use of data visualization and digitalization, including infographics, motion graphics, dashboards, scorecards, factsheets, etc.
• Good verbal, listening, writing, social media and interpersonal skills essential for effective interaction among stakeholders in a broad range of activities.