Data Analyst

Key Responsibilities:

• Data Collection & Preparation:
  
• Extract, clean, and preprocess data from various sources, including MongoDB databases and other structured and unstructured data formats.
• Perform data wrangling tasks to ensure data consistency and quality.
• Data Analysis:
  
• Apply statistical and machine learning techniques to analyze complex datasets and identify trends, patterns, and anomalies.
• Develop and implement algorithms for data analysis, using Python libraries such as pandas, numpy, and matplotlib.
• Data Visualization:
  
• Design and create data visualizations using Python libraries like Matplotlib, Seaborn, or Plotly to communicate insights effectively.
• Use Jupyter Notebooks for interactive data analysis and sharing findings with both technical and non-technical stakeholders.
• Database Management & Querying:
  
• Leverage MongoDB for efficient storage and retrieval of data, ensuring optimal database performance.
• Write complex MongoDB queries and optimize them for large-scale data operations.
• Reporting & Communication:
  
• Create regular reports, dashboards, and presentations to communicate data-driven insights to stakeholders.
• Work closely with business units to understand requirements and deliver actionable insights.
• Collaboration & Continuous Learning:
  
• Collaborate with data engineers, data scientists, and other team members to enhance data pipeline efficiency and quality.
• Stay up to date with industry trends and technologies related to data analysis, machine learning, and big data.