Job Description We are looking for an experienced Python / R Data Analyst with 3+ years of hands-on experience in Python, R, data analysis, statistical modeling, and data visualization. The ideal candidate will analyze complex datasets, identify meaningful insights, and work with business and technical teams to support data-driven decision-making. Key Responsibilities Analyze large and complex datasets using Python and R . Develop data analysis and statistical models to identify trends, patterns, and business insights. Write clean, efficient, and reusable Python and R code for data processing and analysis. Perform data cleaning, transformation, validation, and exploratory data analysis (EDA). Use Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data analysis and visualization. Use R packages such as tidyverse, dplyr, ggplot2, and Shiny for analysis and visualization. Develop dashboards, reports, and visualizations to communicate analytical findings. Work with SQL databases to extract and analyze data. Collaborate with business stakeholders, data engineers, and technical teams to understand requirements. Present analytical findings and recommendations to technical and non-technical stakeholders. Ensure data quality, accuracy, and consistency across analytical outputs. Required Qualifications 3+ years of professional experience with Python. 3+ years of professional experience with R. Strong experience with Pandas, NumPy, Matplotlib, and Seaborn . Strong knowledge of R, Tidyverse, dplyr, and ggplot2 . Strong SQL skills and experience working with relational databases. Experience with data cleaning, manipulation, and exploratory data analysis. Strong understanding of statistics and data analysis techniques. Experience creating data visualizations and analytical reports. Strong problem-solving and analytical skills. Excellent communication and stakeholder-management skills. Preferred Qualifications Experience with Machine Learning and predictive analytics. Experience with Scikit-learn or other Python ML libraries. Experience with R Shiny . Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform . Experience with Tableau or Power BI. Experience working in Agile/Scrum environments.