Data Analyst - R/Python

Responsibilities :

Data Collection and Cleaning :

- Gather data from various sources (databases, APIs, spreadsheets, etc.) and ensure data accuracy and integrity.

- Clean, transform, and prepare data for analysis, addressing missing values, inconsistencies, and outliers.

- Develop and maintain data pipelines to automate data extraction and transformation processes.

Data Analysis and Interpretation :

- Perform in-depth data analysis using statistical techniques and tools to identify trends, patterns, correlations, and anomalies.

- Develop and apply quantitative and qualitative data analysis methods.

- Interpret data analysis results and provide meaningful insights and recommendations.

Reporting and Visualization :

- Design and develop insightful and user-friendly reports, dashboards, and visualizations using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn).

- Communicate complex data findings clearly and concisely through compelling visualizations and presentations.

- Automate report generation and distribution processes.

Collaboration and Communication :

- Collaborate closely with business stakeholders across different departments to understand their data needs and business questions.

- Present data findings and recommendations to technical and non-technical audiences in a clear and understandable manner.

- Participate in cross-functional projects to provide data-driven insights.

Data Quality and Governance :

- Contribute to the development and implementation of data quality standards and governance policies.

- Monitor data quality and identify areas for improvement.

Tool Proficiency :

- Demonstrate strong proficiency in data analysis tools and programming languages such as SQL, Python (with libraries like Pandas, NumPy), and statistical software (e.g., R, SPSS).

- Experience with data visualization tools (e.g., Tableau, Power BI).

- Familiarity with cloud-based data platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark) is a plus.

Business Acumen :

- Develop a strong understanding of the business domain and how data insights can drive strategic decisions.

- Translate business questions into analytical frameworks and identify relevant data sources.

Qualifications :

- Bachelor's or Master's degree in a quantitative field such as Computer Science, or a related discipline.

- 5+ years of professional experience as a Data Analyst.

- Proven ability to collect, clean, analyze, and interpret complex datasets.

- Strong proficiency in SQL for data querying and manipulation.

- Excellent skills in Python (with Pandas, NumPy) or R for data analysis and statistical modeling.

- Hands-on experience with data visualization tools (e.g., Tableau, Power BI).

- Solid understanding of statistical concepts and techniques.

- Strong communication and presentation skills, with the ability to convey data insights effectively to diverse audiences.

- Excellent problem-solving and analytical skills.

- Ability to work independently and collaboratively within a team environment.

Preferred Qualifications :

- Experience with cloud-based data platforms (e.g., AWS, Azure, GCP).

- Familiarity with big data technologies (e.g., Hadoop, Spark).

- Experience with machine learning basics.

- Experience with data warehousing concepts