Key Responsibilities:
- Data Analysis & Strategic Insights:
- Interpret complex datasets using advanced statistical techniques and provide actionable reports to leadership and stakeholders.
- Identify trends, patterns, and correlations in data to drive strategic program decisions.
- Develop predictive models and analyses to optimize resource allocation and program effectiveness.
- Conduct impact assessments and performance evaluations.
- Data Visualization & Communication:
- Design and build interactive dashboards using Tableau, Power BI, Looker, or Sigma.
- Create compelling visual narratives that translate complex data into accessible insights.
- Present analytical findings to senior management, program teams, and external partners.
- Develop automated reporting systems for ongoing monitoring and evaluation.
- Data Infrastructure Development:
- Design and implement robust databases, data collection systems, and analytics pipelines.
- Develop ETL/ELT processes using modern frameworks such as Apache Airflow, Talend, or dbt.
- Acquire and integrate data from primary and secondary sources.
- Establish data governance protocols ensuring quality, security, and compliance.
- Data Quality Assurance:
- Clean, validate, and structure data with meticulous attention to accuracy.
- Review reports, printouts, and performance indicators to identify and resolve data integrity issues.
- Implement automated quality checks and monitoring systems.
- Document data processes and maintain comprehensive data dictionaries.
- Cross-Functional Collaboration:
- Partner with program teams to understand analytical needs and deliver tailored solutions.
- Work closely with management to prioritize business intelligence requirements.
Required Qualifications:
- Education & Experience:
- Bachelor’s/Masters degree in data science, Statistics, Computer Science, Mathematics, Economics, or related field (recent graduates and graduating students encouraged to apply).
- 0-2 years of professional experience (internships, co-ops, and academic projects count).
- Demonstrated ability to work with data through coursework, projects, or professional experience.
- Technical Skills:
- Proficiency in SQL for data extraction, manipulation, and analysis.
- Advanced Microsoft Excel skills including pivot tables, VLOOKUP, macros, and statistical functions.
- Experience with at least one modern business intelligence tool (Tableau, Power BI, Looker, Sigma, or similar).
- Working knowledge of Python (pandas, NumPy, matplotlib) or R for statistical analysis.
- Understanding of data modeling, database design, and data architecture principles.
- Familiarity with statistical concepts and methodologies.
Preferred Qualifications:
- Experience with cloud analytics platforms (AWS, Google Cloud Platform, Azure).
- Knowledge of ETL/ELT tools and data pipeline development.
- Familiarity with version control systems (Git/GitHub).
- Understanding of machine learning concepts and applications.
- Experience with additional statistical packages (SPSS, SAS) or programming languages (JavaScript, XML).
- Background in A/B testing, experimental design, or causal inference.
- Previous experience in the nonprofit, social impact, or development sector.
