<div>ROLE OVERVIEW The Data Analyst serves as a full-stack project lead responsible for independently managing agricultural data projects end-to-end, while also owning cross-team analytics, reporting, and dashboarding standards. This is a dual-mandate role: you will lead your own projects (running data quality checks, producing analyses, delivering client-facing reports and dashboards) and simultaneously define what excellent analytics and visualization looks like across the entire team.This role is ideal for a data professional who combines strong analytical skills with a passion for visual storytelling and a desire to shape team-wide standards and mentor junior talent. KEY RESPONSIBILITIESA. Project Leadership (Assigned Projects)<ul><li>Lead end-to-end execution of assigned agricultural data projects, from data quality checks through final client deliverables.</li><li>Create and monitor data quality checks using established DQC frameworks, ensuring data integrity across all project phases.</li><li>Produce project-specific reports, analyses, and  dashboards for client and internal consumption.</li><li>Manage and assign daily tasks to one Junior Data Analyst, ensuring timely completion and quality of work.</li><li>Step in to execute DQCs directly when necessary.</li><li>Own all client-facing deliverables for assigned projects (subject to peer and management review).</li><li>Manage field team orientation and training on DQC frameworks for assigned projects.</li><li> </li></ul>B. Analytics &amp; Dashboarding Standards (Cross-Team)<ul><li>Design and build Amazon QuickSight dashboards for all team projects, regardless of project lead assignment.</li><li>Create and maintain reusable dashboard templates, visualization standards, and reporting best practices.</li><li>Define and enforce formatting standards for all team reports and client-facing analytics outputs.</li><li>Peer-review reports and visualizations produced by other team analysts to ensure consistency and quality.</li><li>Serve as the team’s final authority on analytics and dashboard quality standards.</li><li>Maintain the Analytics &amp; Reporting Knowledge Base as a living resource for the team.</li><li>Train the entire team on QuickSight and visualization tools and best practices.</li><li>Build automated reporting pipelines to reduce manual effort and improve consistency. </li></ul> C. Review &amp; Mentoring<ul><li>Review DQC execution, reports, and analyses produced by peer analyst on their projects. </li><li>Accept reciprocal review of your own work by the Associate Manager or peer analyst.</li><li>Directly mentor the Junior Data Analysts. </li></ul> REQUIRED QUALIFICATIONS<ul><li>Bachelor’s degree in Data Science, Statistics, Computer Science, Actuarial Science, Economics, or a related quantitative field.</li><li>3+ years of experience in data analysis, business intelligence, or a related analytical role. </li><li>Demonstrated proficiency in SQL and at least one programming language (Python or R) for data manipulation and analysis.</li><li>Hands-on experience building dashboards and visualizations using BI tools (Amazon QuickSight, Tableau, Power BI, or similar).</li><li>Strong understanding of data quality principles, validation logic, and data cleaning workflows.</li><li>Experience producing client-facing reports and analytical deliverables with high attention to detail.</li><li>Excellent written and verbal communication skills, with the ability to translate complex data into clear insights. </li></ul> PREFERRED QUALIFICATIONS<ul><li>Experience in agricultural data, insurance, remote sensing, or development sector analytics.</li><li>Familiarity with Amazon QuickSight specifically (templates, calculated fields, parameters).</li><li>Experience with geospatial data or tools (QGIS, GeoPandas, Google Earth Engine).</li><li>Track record of creating reusable templates, SOPs, or knowledge base documentation for analytics teams.</li><li>Experience mentoring or supervising junior analysts.</li><li>Familiarity with survey design tools (ODK, SurveyCTO, KoboToolbox) and field data collection workflows. </li></ul> KEY COMPETENCIES<ul><li>Analytical Rigor: Ability to identify data anomalies, design validation rules, and ensure accurate outputs.</li><li>Visual Communication: Skill in designing intuitive dashboards and visualizations that drive decision-making.</li><li>Ownership Mindset: Proactive accountability for deliverable quality and team standards.</li><li>Collaboration: Willingness to peer-review, share knowledge, and contribute to a culture of continuous improvement.</li><li>Mentoring &amp; Leadership: Ability to guide junior team members, provide constructive feedback, and build capability. </li></ul> PERFORMANCE INDICATORS<ul><li>On-time delivery of client-facing dashboards and reports for assigned projects.</li><li>Dashboard adoption and client satisfaction scores.</li><li>Quality and completeness of Analytics &amp; Reporting Knowledge Projects.</li><li>Timeliness and thoroughness of peer reviews conducted on team deliverables. </li></ul> To learn more about Pula: ● TED Talk: Crop Insurance, an Idea Worth Seeding ● New York Times: He Grew up on a Farm. Now, He Helps Protect Them ● The Economist: The Poor, Who Most Need Insurance, Are Least Likely to Have It</div>

Reimagining agricultural insurance to protect smallholders worldwide. At Pula, we are radically restructuring insurance, using technology and parametric insurance to insure the previously unbanked, uninsured, untapped market of 1.5 billion smallholders worldwide. We work across Africa and Asia, and in 2019 alone, we facilitated crop and livestock insurance cover to 1.1mln farmers and have offered our products in 11 markets . Since starting in 2015, our products have impacted over 4.9 Million smallholder farmers. Our Founders work in insurance has been recognized by several international awards including the Financial Times/IFC Award for Sustainable Finance, the Singapore Fintech Festival, Womens World Banking, Credit Suisse, and InsureTech3.0. We partner with organisations across multiple value chains, from agriculture to renewable energy including Fortune 500 Companies, Global NGO&rsquo;s, Microfinance Instructions, Research Institutions, and Governments to help provide households the protection they need in an increasingly unpredictable climate.

Data Analyst

<div>ROLE OVERVIEW The Data Analyst serves as a full-stack project lead responsible for independently managing agricultural data projects end-to-end, while also owning cross-team analytics, reporting, and dashboarding standards. This is a dual-mandate role: you will lead your own projects (running data quality checks, producing analyses, delivering client-facing reports and dashboards) and simultaneously define what excellent analytics and visualization looks like across the entire team.This role is ideal for a data professional who combines strong analytical skills with a passion for visual storytelling and a desire to shape team-wide standards and mentor junior talent. KEY RESPONSIBILITIESA. Project Leadership (Assigned Projects)<ul><li>Lead end-to-end execution of assigned agricultural data projects, from data quality checks through final client deliverables.</li><li>Create and monitor data quality checks using established DQC frameworks, ensuring data integrity across all project phases.</li><li>Produce project-specific reports, analyses, and  dashboards for client and internal consumption.</li><li>Manage and assign daily tasks to one Junior Data Analyst, ensuring timely completion and quality of work.</li><li>Step in to execute DQCs directly when necessary.</li><li>Own all client-facing deliverables for assigned projects (subject to peer and management review).</li><li>Manage field team orientation and training on DQC frameworks for assigned projects.</li><li> </li></ul>B. Analytics &amp; Dashboarding Standards (Cross-Team)<ul><li>Design and build Amazon QuickSight dashboards for all team projects, regardless of project lead assignment.</li><li>Create and maintain reusable dashboard templates, visualization standards, and reporting best practices.</li><li>Define and enforce formatting standards for all team reports and client-facing analytics outputs.</li><li>Peer-review reports and visualizations produced by other team analysts to ensure consistency and quality.</li><li>Serve as the team’s final authority on analytics and dashboard quality standards.</li><li>Maintain the Analytics &amp; Reporting Knowledge Base as a living resource for the team.</li><li>Train the entire team on QuickSight and visualization tools and best practices.</li><li>Build automated reporting pipelines to reduce manual effort and improve consistency. </li></ul> C. Review &amp; Mentoring<ul><li>Review DQC execution, reports, and analyses produced by peer analyst on their projects. </li><li>Accept reciprocal review of your own work by the Associate Manager or peer analyst.</li><li>Directly mentor the Junior Data Analysts. </li></ul> REQUIRED QUALIFICATIONS<ul><li>Bachelor’s degree in Data Science, Statistics, Computer Science, Actuarial Science, Economics, or a related quantitative field.</li><li>3+ years of experience in data analysis, business intelligence, or a related analytical role. </li><li>Demonstrated proficiency in SQL and at least one programming language (Python or R) for data manipulation and analysis.</li><li>Hands-on experience building dashboards and visualizations using BI tools (Amazon QuickSight, Tableau, Power BI, or similar).</li><li>Strong understanding of data quality principles, validation logic, and data cleaning workflows.</li><li>Experience producing client-facing reports and analytical deliverables with high attention to detail.</li><li>Excellent written and verbal communication skills, with the ability to translate complex data into clear insights. </li></ul> PREFERRED QUALIFICATIONS<ul><li>Experience in agricultural data, insurance, remote sensing, or development sector analytics.</li><li>Familiarity with Amazon QuickSight specifically (templates, calculated fields, parameters).</li><li>Experience with geospatial data or tools (QGIS, GeoPandas, Google Earth Engine).</li><li>Track record of creating reusable templates, SOPs, or knowledge base documentation for analytics teams.</li><li>Experience mentoring or supervising junior analysts.</li><li>Familiarity with survey design tools (ODK, SurveyCTO, KoboToolbox) and field data collection workflows. </li></ul> KEY COMPETENCIES<ul><li>Analytical Rigor: Ability to identify data anomalies, design validation rules, and ensure accurate outputs.</li><li>Visual Communication: Skill in designing intuitive dashboards and visualizations that drive decision-making.</li><li>Ownership Mindset: Proactive accountability for deliverable quality and team standards.</li><li>Collaboration: Willingness to peer-review, share knowledge, and contribute to a culture of continuous improvement.</li><li>Mentoring &amp; Leadership: Ability to guide junior team members, provide constructive feedback, and build capability. </li></ul> PERFORMANCE INDICATORS<ul><li>On-time delivery of client-facing dashboards and reports for assigned projects.</li><li>Dashboard adoption and client satisfaction scores.</li><li>Quality and completeness of Analytics &amp; Reporting Knowledge Projects.</li><li>Timeliness and thoroughness of peer reviews conducted on team deliverables. </li></ul> To learn more about Pula: ● TED Talk: Crop Insurance, an Idea Worth Seeding ● New York Times: He Grew up on a Farm. Now, He Helps Protect Them ● The Economist: The Poor, Who Most Need Insurance, Are Least Likely to Have It</div>

Data Analyst

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PULA

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