Key skills
PythonSQLRMachine LearningMLOpsData EngineeringAnalyticsSnowflakeDatabricksSparkAirflowdbtAWSAzureGoogle Cloud
About this role
Job Title: Data Scientist / Data Engineer
Location: Remote
Location: Remote
Position Summary:
Hands-on data professional responsible for end-to-end data engineering, analytics, and model development for development sector programs. Covers data pipeline architecture, dataset preparation, dashboarding, and analytics workflow deployment.
Engagement Details:
- Location: Home-based, remote. No office attendance required.
- Engagement type: Independent consultant or sub-contractor under company.
- Duration: Level of Effort basis per task order. Initial bench placement is for 12 months with extensions possible.
- Travel: Only when a specific task order requires it. All travel pre-approved and reimbursed.
Key Responsibilities:
- Design and build data pipelines, data warehouses, and analytics platforms supporting development programs.
- Prepare, clean, and transform datasets from country information systems, surveys, administrative records, and external sources.
- Develop analytics models, dashboards, and reporting layers for program monitoring, evaluation, and decision support.
- Build and deploy machine learning models in production environments, including MLOps practices for model monitoring and retraining.
- Work with cloud platforms such as Azure, AWS, Google Cloud Platform and open-source data stacks to deliver scalable analytics workflows.
- Document data flows, lineage, and governance controls for donor reporting and compliance.
Required Qualifications:
- Bachelor's degree required in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related field. Master's degree preferred.
- Minimum 7 years of relevant professional experience, with 5 to 10 plus years specifically in data engineering, analytics, or model development.
- Proficiency with Python, R, SQL, REST APIs, cloud platforms, and modern data pipeline architectures including dbt, Airflow, Spark, Databricks, or Microsoft Fabric.
- Demonstrated experience preparing datasets, dashboards, models, or analytics workflows for production deployment.
- Familiarity with health, education, or social sector data standards preferred, including DHIS2, FHIR, CSPro.
- Experience working in low and middle income countries or public sector environments preferred.
Preferred Certifications:
- Azure Data Engineer
- AWS Data Analytics Specialty
- Databricks or Snowflake
- CAP (Certified Analytics Professional)