Job Responsibilities (not limited to):
- Write clean, efficient Python scripts to process, clean, and analyze datasets.
- Perform daily data wrangling using Pandas and NumPy.
- Extract and integrate data from APIs and external systems.
- Conduct statistical analysis and identify trends or anomalies in datasets.
- Build and maintain lightweight data pipelines and analytical workflows.
- Collaborate with team members to solve data challenges and improve processes.
- Contribute to maintaining clear, well-documented and maintainable code.
Requirements:
Industry Experience:
- 2+ years of professional experience working with Pandas and NumPy
- 1+ year of professional experience using Scikit-Learn
- Strong experience with Matplotlib and statistical data analysis
- Strong Python development skills
- Experience working with structured and unstructured datasets
- Excellent problem-solving and analytical thinking skills
- Strong communication skills and ability to work within a remote team environment
Required Skills:
- Strong Python scripting skills with the ability to write code from scratch without relying heavily on prebuilt frameworks
- 2+ years of professional experience using Pandas and NumPy for data manipulation
- Experience performing data cleaning, transformation, and analysis
- Solid understanding of Python data structures, indexing, and data operations
- Experience working with APIs and JSON data
- Experience using Matplotlib or similar libraries for data visualization
- Strong problem-solving skills and ability to debug data workflows
- Comfortable working in a fast-paced, collaborative remote environment
Advantageous Skills:
- Experience using Scikit-Learn for basic machine learning tasks
- Familiarity with statistical analysis techniques (e.g., outlier detection, distribution analysis)
- Experience working with large or messy datasets
- Exposure to Power BI or reporting tools
- Experience with Microsoft Azure, XGBoost, or PyTorch