Data Analytics Team

 Data Scientists

• Skills: Statistical analysis, machine learning algorithms, data wrangling
   
• Tools: Python (Pandas, scikit-learn), R, SQL, Jupyter notebooks
   
• Role: Analyze and interpret complex data, build predictive models, generate insights to support decision-making
   

Machine Learning Engineers

• Skills: Model development, deployment, optimization
   
• Tools: TensorFlow, PyTorch, ML pipelines, cloud ML platforms (AWS SageMaker, Azure ML)
   
• Role: Take data science models and productionize them; build scalable ML solutions
   

Data Engineers

• Skills: ETL pipelines, big data frameworks, data warehousing
   
• Tools: Hadoop, Spark, Apache Kafka, AWS/GCP/Azure data tools
   
• Role: Build and maintain data infrastructure and pipelines for efficient data flow and storage
   

AI Research Scientists (for cutting-edge projects)

• Skills: Deep learning, NLP, computer vision, algorithm research
   
• Tools: Advanced ML frameworks, research publications
   
• Role: Innovate new AI algorithms and techniques
   

Business Intelligence (BI) Analyst / Data Analysts

• Skills: Data visualization, reporting, business metrics analysis
   
• Tools: Tableau, Power BI, Excel, SQL
   
• Role: Translate data insights into business strategies, create dashboards and reports
   

Project Managers / Product Owner

• Skills: Agile methodologies, stakeholder management, tech knowledge
   
• Role: Manage project scope, timelines, client communication, ensure deliverables meet business needs
   

Cloud Architect / DevOps Engineer (for ML model deployment and scaling)