Data Scientist

Data Scientist

Job Overview

The Data Scientist will manage the processes of accurate data collection, processing, modeling, and analysis. The ideal candidate will have a strong ability to synthesize valuable insights from raw data, and the communication skills to effectively disseminate information across the team and organization.

Responsibilities

• Define, design, and implement research projects harnessing Big Data to improve programming and inform decision making.
• Develop and deploy qualitative and quantitative data collection tools, analyze, and present the data as required.
• Explore and deploy relevant software required for evaluating and presenting data appropriately.
• Develop high quality written technical reports and visualize data findings creatively in a variety of formats.
• Lead capacity-building of the program team on technical expertise in research, data analysis, and data science/artificial intelligence.
• Support development of high-value or complex proposals or bids including proposal writing Design architecture, deploy and maintain supporting infrastructure for Idmibok’s analytic platforms.
• Automate the deployment, administration and operations of the infrastructure and analytic platforms.
• Build and maintain standard authentication and access patterns for integrations within Idmibok’s broader data/technology ecosystem.
• Partner with the Information Technology team to maintain and support application licensing and software distribution.
• Provide analytics tools and platforms subject matter expertise to staff/team.
• Support the rollout of analytical solutions through training of field users and creation of training material.
• Provide ad-hoc support of various growth initiatives including qualitative research, survey design, web development, and more.

Qualifications

• Bachelor’s degree or a Master’s degree in Data Analytics, Data Science, Statistics, Mathematics or Computer Science/IT.
• 3-4 years of experience in a BI, data science or analyst role in an organization.
• Knowledge of applied statistics, specifically experimental design, and study with statistics packages e.g. SPSS, STATA, R, Python, etc.
• Knowledge of data science techniques, such as machine learning, AI and statistical modeling.
• Knowledge of GIS mapping and spatial data analysis tools (ArcGIS, QGIS, etc.) is desirable.
• Knowledge of cloud computing for deploying models (AWS, Microsoft Azure. Google Cloud, etc.) is a plus.
• Advanced use of Microsoft Excel and working with data visualization tools e.g. Tableau, Power BI.
• Prior experience with the development of data pipelines and automation e.g. ETL, APIs, etc.
• Proficiency in using programming skills in Python and/or R to perform data analysis.
• Strong NumPy/PANDAS skills and SQL database usage.
• Experience with mobile data collection tools e.g. ODK, Kobo, is desirable.
• Strong analytical and quantitative skills with the ability to think outside the box.
• Excellent communication and interpersonal skills with an emphasis on taking a data-focus approach.
• Demonstrated ability to multi-task, prioritize, self-start, contribute under pressure, and meet tight deadlines.