AI, Python engineer

Job Description – Data Analytics & Data Science Specialist

Key Responsibilities:

• Analyze, assess, and interpret large datasets using advanced analytics techniques on modern data platforms.
• Prepare reports, dashboards, and insights to support business decision-making.
• Evaluate data structures, data quality, and business processes to identify improvement opportunities.
• Design, develop, and maintain effective data models to support analytical and operational requirements.
• Apply machine learning techniques and integrate analytical outcomes into business solutions and processes.
• Perform data transformation activities including data enrichment, blending, expansion, filtering, consolidation, and cleansing.
• Prepare cost-benefit analyses and support techno-economic evaluations for data-driven initiatives.
• Develop and present recommendations, decision-making proposals, and actionable insights to stakeholders.
• Participate in the development of assessment, monitoring, and steering tools for handling multiple data sources and ensuring data availability.
• Manage end-to-end analytics and data science projects, ensuring timely delivery and alignment with business objectives.
• Collaborate with cross-functional teams to implement data-driven solutions and drive continuous improvement.

Required Skills & Qualifications

• Strong experience in Data Analytics, Data Science, or related fields.
• Hands-on experience with data modeling, data transformation, and data management techniques.
• Knowledge of Machine Learning, Statistical Analysis, and Predictive Modeling.
• Experience working with modern data platforms such as Azure, AWS, Google Cloud, Databricks, Snowflake, or similar.
• Proficiency in SQL and programming languages such as Python or R.
• Experience with data visualization and reporting tools such as Power BI, Tableau, or equivalent.
• Strong analytical, problem-solving, and stakeholder management skills.
• Experience managing analytics or data-driven projects.

Preferred Qualifications

• Experience in cloud-based data ecosystems and big data technologies.
• Understanding of data governance, data quality, and data architecture principles.
• Certifications in Data Analytics, Data Science, Machine Learning, Azure, AWS, or related technologies are an advantage.

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