Data Scientist

Job Summary

The Data Scientist will lead the development of appropriate data products for CRS’s program and sector teams, in line with industry best practices. They work as part of cross-functional data science team and will coordinate with data scientists, program and sector staff to identify opportunities to leverage data science within specific programmatic sectors, lead the search and identification of data sources, support the preparation of data, and develop and maintain relevant data products. They also provide technical assistance to project and sector teams in interpreting and using the results of the analyses. The Data Scientist’s expertise, leadership, and influence will be key in determining how effective, adaptive and innovative CRS’ data science practices are across the globe.

Roles and Key Responsibilities

• Contribute to the identification of opportunities to apply data science to specific projects and sectors 
• Lead the search and identification of new data sources, the ingestion, preparation, and onboarding of data for operational and programmatic Use Cases
• Engaging with sector teams, review data collected and make decisions on how to transform data, what approaches to apply when analyzing data, and recommendations for data cleansing
• Lead the development of appropriate data products for CRS’s program and sector teams, following industry best practices and through engagement with sector teams
• Lead the maintenance and development of data products for operational and programmatic Use Cases, ensuring both data and models are functioning properly, and cataloged, accessible, and used appropriately
• Share data insights with to sector and project teams and provide technical assistance in interpreting and using results from data analyses.
• Contribute to the knowledge management and learning agenda in data science through helping implement conditions for collective learning that ensure the capturing, documenting, and sharing of key successes, promising practices, and lessons learned.

Key Working Relationships:  

• Internal – Colleagues within the Data Science Centre of Practice; Members of the ICT4D team; Regional, country, and project staff; data science colleagues; Senior Advisor for data science; Director and Deputy Director for MEAL; Global and Regional MEAL Technical Advisors
• External - peers in other NGOs, data science consultants

Basic Qualifications (BQs)

Education and Experience 

• Master’s degree in mathematics, statistics, or data science
• Minimum five years of work experience as a data scientist or data analyst
• Demonstrable experience with linear algebra, probability theory, and statistical inference
• Demonstrable programming experience with Python or R
• Familiarity with databases and SQL 
• Familiarity with reporting software such as Power BI, Tableau, or others
• Demonstrable experience with machine learning algorithms and ability to solve complex data problems
• Experience with conducting geospatial data analyses and/or spatial analysis (preferred)

Required Languages - English, French and/or Spanish is a plus.

Travel- Must be willing and able to travel up to 35%. 

Knowledge, Skills and Abilities (KSAs)

• Excellent relationship management skills with ability to influence and get buy-in from people not under direct supervision and to work with individuals in diverse geographical and cultural settings.
• Very strong strategic, analytical, problem-solving and systems thinking skills with capacity to see the big picture and ability to make sound judgment
• Very strong written and oral communication skills, particularly in terms of communicating complex technical approaches to no-technical audiences 
• Very strong presentation, facilitation, training, mentoring, and coaching skills
• Proactive, resourceful and results-oriented

Preferred Qualifications – (If applicable)

• Experience working in international development and humanitarian assistance, ideally with an international NGO
• Experience with matrixed reporting and working in fusion teams
• Understanding of technical principles and concepts in program  data methods and applications, such as research, monitoring and evaluation, o