Senior Data Analyst

Data Analyst - Good SQL, Tableau, Python Data Analyst to join our team. As a Data Analyst, you will play a crucial role in transforming raw data into actionable insights that drive business decisions. You will be responsible for collecting, cleaning, analyzing, and visualizing data to uncover trends, patterns, and opportunities. Responsibilities: Data Collection and Preparation: Gather data from various sources, including databases, APIs, and spreadsheets. Clean and pre-process data to ensure accuracy and consistency. Transform data into a suitable format for analysis. Data Analysis: Utilize statistical techniques to analyze data and identify key trends and patterns. Perform data mining and exploratory data analysis to uncover hidden insights. Develop and implement data models to predict future trends and outcomes. Data Visualization: Create compelling data visualizations, including charts, graphs, and dashboards, using tools like Tableau. Communicate complex data insights effectively to both technical and non-technical audiences. Data-Driven Insights: Collaborate with business stakeholders to understand their needs and translate them into data-driven solutions. Provide actionable recommendations based on data analysis. Monitor key performance indicators (KPIs) and track progress towards business goals. Automation and Optimization: Automate routine tasks using Python scripting to improve efficiency. Optimize data pipelines and processes to ensure timely and accurate results. Qualifications: Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. Strong proficiency in SQL for data querying and manipulation. Experience with data visualization tools such as Tableau. Programming skills in Python, including libraries like Pandas, NumPy, and Scikit-learn. Excellent analytical and problem-solving skills. Strong attention to detail and accuracy. Excellent communication and presentation skills. Ability to work independently and as part of a team. Preferred Qualifications: Experience with data warehousing and ETL processes. Knowledge of machine learning and statistical modeling techniques. Experience with cloud-based data platforms (e.g., AWS, GCP, Azure).