Data Processing Officer - Ghana Statistical Service

The Ghana Statistical Service is the government agency charged with the responsibility of providing quality, relevant, accurate, and timely statistical information for the purpose of national development. It has offices in all the sixteen (16) regions of the country.

The Service invites applications from qualified Ghanaians who are goal-oriented and results-driven to apply for the under-listed positions within the Service as a Data Processing Officer.

Job Purpose

To provide technical support to automate statistical processes, enhance precision in the production of statistical outputs and harness new data sources to improve the scope and scale of data products accessible to policymakers and other data users.

Duties and Responsibilities

The specific duties and responsibilities are as follows:

• Transform diverse data formats including spatial, administrative, big data and pictorial into analyzable forms using contemporary data mining and artificial intelligence techniques
• Develop algorithms and employ machine learning techniques to analyse complex, large and multiple datasets
• Compile and provide adjustment factors to address blases across different sources and modes of data collection
• Forecast outcomes of a wife range of socio-demographic, behavioural and economic variables
• Adapt off-the-shelf tools for monitoring and evaluating a wide range of data within Ghana Statistical Services across the National Statistical system and national and sub-national policy-making units

Qualification Required & Experience

• At least a Master’s degree from an accredited tertiary institution in any of the following: Statistics, Technical Demography, Engineering, Computer Science, Geography, Economics, Mathematics, Sociology and related fields
• Must have completed a one-year national service
• Must have at least 2 years of work experience in the data science landscape, which includes Data Analyst, Data Engineer and Machine learning Engineer at a reputable organisation

Competencies and Skills

• Programming knowledge (R, Python,SQL etc)
• Applying machine learning techniques such as clustering, algorithms, decision tree learning and artifical neural networks
• Handling, management and analysis of traditional and non-traditional data
• Modelling complex socio-demographic, behavioural and economic conceptual frameworks
• Employing advanced statistical and econometric estimation techniques including parametric and non-parametric regression models
• Writing manuscripts, journal articles and policy briefs