Responsibilities:
Data Collection and Management:
Collect and curate data from various sources including but not limited to Google Sheets databases and APIs.
Organize clean and maintain datasets to ensure data integrity and accessibility.
Statistical Analysis and Modeling:
Apply statistical methods to interpret data trends and patterns.
Develop and execute statistical models to derive actionable insights.
Provide answers and context required for operational and strategic decisionmaking by the senior team.
Data Visualization:
Create visual representations (charts graphs dashboards) to effectively communicate datadriven insights including daily data dashboards for team leads and decisionmaking.
Collaboration and Support:
Collaborate with teams to understand data requirements and provide analytical support.
Assist in the design and implementation of datadriven strategies and solutions.
Quality Assurance:
Perform quality checks on data outputs and analyses to ensure accuracy.
Requirements
Qualifications:
1. Bachelors degree in a relevant field such as Statistics Mathematics or Computer Science.
2. Proficiency in data manipulation tools (e.g. SQL Python or R) and data visualization tools (e.g. Tableau Power BI).
3. Strong attention to detail and ability to work with large datasets.
4. Excellent communication skills to convey complex findings to nontechnical stakeholders.
5. Problemsolving mindset and ability to think critically about business challenges.
6. Familiarity with sales metrics KPIs and performance indicators.
7. Stay informed about industry best practices and emerging trends in data analysis.
Preferred Skills:
1. Experience with machine learning techniques for predictive analytics.
2. Knowledge of CRM systems and their data structures.
3. Understanding of statistical concepts and hypothesis testing
Benefits
Benefits:
1. Fuel Allowance
2. Medical Allowance
3. Communication Allowance
4. Lunch at the office
5. Yearly bonus (based on performance)
Qualifications: 1. Bachelor's degree in a relevant field such as Statistics, Mathematics, or Computer Science. 2. Proficiency in data manipulation tools (e.g., SQL, Python, or R) and data visualization tools (e.g., Tableau, Power BI). 3. Strong attention to detail and ability to work with large datasets. 4. Excellent communication skills to convey complex findings to non-technical stakeholders. 5. Problem-solving mindset and ability to think critically about business challenges. 6. Familiarity with sales metrics, KPIs, and performance indicators. 7. Stay informed about industry best practices and emerging trends in data analysis. Preferred Skills: 1. Experience with machine learning techniques for predictive analytics. 2. Knowledge of CRM systems and their data structures. 3. Understanding of statistical concepts and hypothesis testing