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Project Officer

3 months ago

Nairobi, Nairobi Area, Kenya Catholic Relief Full time

Catholic Relief Services (CRS) is an international non-governmental organization supporting relief and development work in over 99 countries around the world.

CRS programs assist persons on the basis of need, regardless of creed, ethnicity or nationality and works through local church and non-church partners to implement its programs
Job Summary

The Project Officer – Data Analyst plays a critical role in ensuring Nawiri effectively uses its data for making evidence-based decisions and drive continuous improvement.

Nawiri collects a lot of data and current utilization is currently low besides reporting.

The data analyst will work closely with the sector teams to analyze data further and develop trends, regression analysis and cross tabulations that will be useful in showing the direction of change.

They work closely with the M&E team to ensure that both Nawiri custom and USAID BHA indicators are calculated accurately according to the performance indicator reference sheets (PIRS), correctly tabulated and entered on the indicator performance tracking table (IPTT).

They also verify participant based annual survey (PaBS), Recurrent Resilience Analysis (RRA) data and ensure it is correctly analyzed and reported.

Roles and Key Responsibilities

Participate in designing data collection, cleaning and analysis methods and preprocessing structured and unstructured data to ensure its quality and reliability.

Create and execute machine learning algorithms and statistical models for routine monitoring data and special surveys.

Work with the sector and information and communication technology for development (ICT4D) teams to explore and visualize data to identify patterns, trends, and relationships, and presenting the results and suggestions to relevant parties by using easily understandable visuals and concise reports.

Ensure the effectiveness of data models through rigorous testing and analysis and evaluating the performance of data models and refining them as needed.

Ensure the indicator performance tracking tables (IPTT)/dashboard accurately represent USAID/BHA requirements including indicator calculations from Participant based Annual Survey (PaBS), Recurrent resilience analysis (RRA), and post distribution monitoring (PDMs) amongst others.

Ensure learning consistently accompanies project activities throughout the project cycle through collaboration with other ICT4D professionals, documenting data models, configurations, and procedures to ensure that other team members can understand and maintain the system effectively.

Requirements
Knowledge, Skills, and Abilities

Analysis and problem-solving skills with ability to make sound judgment.

Good relationship management skills and the ability to work closely, influence and get buy-in from staff and local partners.

Proactive, results-oriented, and service-oriented.
Attention to details, accuracy, and timeliness in executing assigned responsibilities.
Presentation, facilitation, training, and mentoring skills.
Strong active listening and communication skills using both formal and informal approaches.
High integrity with ability to manage sensitive information professionally while maintaining confidentiality.
Demonstrated commitment to respect, equity, diversity, and inclusion.

Required Languages:
Excellent verbal and written communication in English, with ability to write reports.

Travel:
Position is based in Nairobi. Must be willing and able to travel to the field up to 40%.

Supervisory Responsibilities:
None

Key Working Relationships

Internal:
Strategic Learning Lead, County-based M&E staff, Project staff, CRS Information and Communications Technology (ICT)/GKIM staff.

External:
Implementing partner M&E officers and consortium partner staff, and peer agencies' staff. USAID and Mercy Corps led Nawiri ICT4D staff.

QUALIFICATIONS
Basic Qualifications

Bachelor's degree in statistics, data science, computer science, or another quantitative field is required. Formal/certification in relational databases and/or advanced visualization platforms is an added advantage. Additional experience may substitute for some education qualifications.

Minimum of 4 years of work experience in project support, ideally in the field of statistics, data science, modelling, and data analysis.

Proficiency in programming languages commonly used in data science, such as Python or R. These languages are used for data manipulation, analysis, visualization, and model development.
Strong understanding of statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and probability theory. Statistical knowledge is crucial for data exploration, model building, and evaluating the significance of results.
Knowledge of machine learning algorithms and techniques for supervised learning, unsupervised learning, and reinforcement learning. This includes algorithms for classification, regression, clustering, dimensionality reduction, and ensemble methods.

Skills in data wrangling and manipulation to clean, preprocess, and transform raw data into a suitable format for analysis.

Proficiency in libraries like Pandas (Python) or dplyr (R) for data manipulation tasks.
Ability to create effective visualizations to communicate insights from data.

Proficiency in data visualization libraries such as Matplotlib, Seaborn, ggplot2, PowerBi, ArcGIS or Plotly for creating plots, charts, and interactive dashboards.

Knowledge of database systems and querying languages like SQL for data extraction and manipulation. Understanding of relational databases, NoSQL databases, and data warehouse concepts
Knowledge of USAID indicators tabulation and calculation.
Experience working with partners, participatory action planning and community engagement.

Experience using MS Windows and MS Office packages (Excel, Word, PowerPoint), Web Conferencing Applications, information management systems, knowledge-sharing networks.

Demonstrated experience in facilitating groups, meetings, and events (both online and in-person), resulting in collaborative decision-making with agreed-upon action items/priorities.