data insighter
3 days ago
The
Data Insighter
plays a key role in turning complex data into meaningful insights that guide business decisions. This involves extracting and analyzing large datasets, crafting clear narratives from data, and supporting internal teams in using analytics tools effectively.
Responsibilities:
- Extract, explore, and manipulate large and complex datasets.
- Help internal stakeholders understand, interpret, and analyze massive data sets.
- Develop analytical methodologies using descriptive and inferential statistical methods for exploratory data analysis.
- Create easy-to-understand narratives and actionable insights from complex data using advanced data visualization and presentation techniques.
- Act as an analytics consultant to internal business users, providing guidance on data, measurement methodology, and analytical techniques.
- Support internal stakeholders in using data and analytical tools to generate and communicate insights.
Engagement Type:
Project-Based (6 Months)
Work Setup:
Remote
Qualifications:
- Education:
Bachelor's degree in Statistics, Mathematics, Computer Science, Information Technology, Economics, or any related field. - Experience:
Solid background in data analysis, statistical modeling, or business intelligence, preferably within a consulting or corporate environment. - Technical Skills:
- Proficiency in
ETL tools
(e.g., Talend, Alteryx, Apache Airflow, or similar) for data extraction and transformation. - Strong command of
SQL
for querying and managing large databases. - Working knowledge of
Python
for data manipulation, analysis, and automation. - Skilled in
data visualization tools
such as Power BI, Tableau, or equivalent platforms. - Analytical Skills:
Strong understanding of descriptive and inferential statistics, hypothesis testing, and data validation techniques. - Communication:
Ability to translate complex analytical findings into clear, actionable insights for non-technical audiences. - Collaboration:
Comfortable working closely with cross-functional teams, providing analytical guidance and data-driven recommendations. - Attention to Detail:
High level of accuracy and commitment to data integrity and quality.
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