Data Analyst, Data Engineering, AI Workflows

Job not on LinkedIn

🔥 13 hours ago

🇰🇪 Kenya – Remote

⏰ Full Time

🟢 Junior

🟡 Mid-level

📉 Data Analyst

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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PULA

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

🌾 Agriculture

🛡️ Insurance

Agriculture • Insurance • Technology

PULA is an agricultural insurance and technology company that designs and delivers innovative insurance and digital products to support smallholder farmers. They provide specialized crop and livestock insurance solutions, along with data services related to yield data collection and EUDR compliance services. Their aim is to help farmers manage yield risks, improve farming practices, and increase incomes. PULA has been recognized globally for its impact and innovation in the insurtech industry.

📋 Description

• Clean, standardise and validate large field datasets including farmer registrations, surveys, polygons and photos • Run data quality checks using the gate-based DQC framework and SOPs, and resolve flagged issues with analysts and field teams • Reconcile collected data against master lists and reference data • Identify and correct defects in data quality checks and recommend SOP improvements • Build and maintain ETL pipelines from collection tools and PostgreSQL/PostGIS databases to analysis outputs and client deliverables • Schedule and monitor automated jobs with logging, incremental loads and failure alerts • Design and document data schemas, validation rules and data dictionaries for country projects • Write clean, version-controlled and tested Python and SQL • Process geospatial data and support compliance checks such as EUDR polygon validation • Set up and maintain AI-assisted workflows using LLM tools for data cleaning, quality checks, report drafting and repetitive analyst tasks • Build OCR and LLM-based document and image extraction pipelines with accuracy verification • Maintain prompts, reusable skills, project context files and runbooks for consistent, auditable AI workflows • Evaluate AI versus deterministic scripts and track cost, accuracy and data privacy risks • Train analysts to use AI tools safely and effectively • Identify project risks and issues, propose practical solutions, and prepare dashboards, reports and delivery files • Develop and evaluate operational processes and procedures • Draft technical documentation, SOPs and training materials, and train analysts and field staff • Provide the manager with daily, weekly and ad-hoc updates

🎯 Requirements

• Bachelor’s degree in Computer Science, Statistics, Data Science, Information Systems, Economics, Geoinformatics, or a related field • Minimum of 2 years of experience in data analysis or data engineering • Demonstrated experience cleaning large, messy field or survey datasets end to end • Portfolio, GitHub profile or work samples showing pipelines or automations built • Strong Python, including pandas and scripting for automation • Strong SQL, with experience in PostgreSQL • Experience building and scheduling ETL pipelines • Experience using Git and working on Linux or cloud servers such as AWS EC2 • Hands-on experience using LLMs and AI tools in real workflows, including prompt design and checking AI outputs for accuracy • Familiarity with mobile data collection tools such as ODK, KoboToolbox, CommCare, or SurveyCTO • Experience with PostgreSQL; PostGIS is a plus • Experience with R is a plus • Experience building agentic or multi-step AI workflows, self-hosted/open-source models, OCR and document extraction, geospatial tools, EUDR/deforestation compliance data, orchestration tools or Docker is nice to have

🏖️ Benefits

• High-performance, multicultural team environment • Opportunities to work on global agricultural insurance projects across Africa, Asia and Latin America • Training analysts and field staff on new systems and AI tools • Professional development through exposure to data engineering, geospatial data, AI workflows and automation