Data Scientist, GivingTuesday
DARO
- Brasil
- Permanente
- Período integral
- Work with a wide range of data types including donation data, transaction records, government and census data, nonprofit tax filings, survey data on perceptions and activity, and philanthropic investment account data, gathered from collaborators and institutional partners in the nonprofit ecosystem
- Deliver and write analyses with actionable insights and communicate these findings to cross functional stakeholders of varying technical levels
- Manage key datasets and improve their usability by creating database dictionaries and user documentation
- Improve existing data processing pipelines, automate recurrent operations on core datasets
- Create impactful data visualisations and interactive data dashboards for stakeholders
- Interest in the nonprofit and philanthropic sector and use of data to promote better social outcomes
- Advanced analytical skills in a research context, conducting exploratory analysis and mapping data flows, integration of datasets, and reviewing data sources and tools
- Experience with statistical methods including hypothesis testing, regression analysis, and sampling techniques for the purposes of social science research (such as economics, mixed methods) and/ or business analytics
- Experience working with scripting languages (Python required) and data querying languages (SQL preferred)
- Solid data visualisation skills and an aptitude for translating technical outputs into compelling stories
- Experience with software development tools and practices (e.g. version control, testing outputs, and applying QA processes)
- Understanding of legislation around privacy and best practices for securing data
- Solid relationship management skills, with the ability to collaborate with a variety of internal and external stakeholders on complex research initiatives
- Outstanding written and oral communication skills in English and an ability to communicate clearly and directly
- Attention to detail and ability to synthesise diverse datasets
- Programming skills: Python, PySpark, SQL, Databricks, Git, pandas
- Data Manipulation and Exploration
- Advanced Modelling: Regressions, Clustering, Dimensionality Reduction, Classification, Bayesian, Time-Series Analysis, prompt engineering
- Experience working with data platforms such as Databricks (or other forms of cloud data lakes/warehouses/lakehouses)
- An advanced degree in a quantitative research-field (definitely not required!). Non-degreed candidates must possess an extensive public record of competent, curiosity-driven data exploration on github, huggingface, kaggle, stackoverflow or similar.