Senior Data Scientist & AI Engineer advancing RLD Foundation’s data strategy in a collaborative environment. Building data infrastructure and conducting analytics to support social impact initiatives.
Responsibilities
Play a central part in advancing the foundation’s data strategy in a highly collaborative environment.
Building and owning RLD Foundation’s core data infrastructure and AI-enabled analytics platform.
Conducting advanced analytics to generate insights that inform grantmaking strategy and organizational learning.
Architect the technical systems that enable high-quality data work across the foundation while also serving as a lead analyst who delivers clear, actionable insights to program teams and leadership.
Contribute to broader data strategy development and selective grantee- and field-facing data capacity building initiatives.
Report to the Director of Data Strategy & Insights and work alongside a Senior Research and Insights Analyst.
Shape systems, tools, and analytical approaches within an early-stage data environment.
Bring technical leadership to the team, with autonomy to architect solutions and make strategic technical decisions.
Requirements
Typically 7+ years of experience in data science, engineering, analytics, AI, or related role
Mission alignment: Demonstrated commitment to social impact and the values of the Foundation
Data infrastructure: Experience with cloud data platforms (e.g., Snowflake, Azure, BigQuery, AWS), data warehouse architecture, and building automated ETL/ELT pipelines (e.g. dbt, Airflow)
Programming expertise: Advanced proficiency in SQL, and Python and/or R for data analysis, modeling, and automation
Data analytics and modeling: Strong foundation in statistical methods, predictive modeling, and machine learning; experience applying these methods to real-world problems
Practical experience with modern AI/ML concepts (LLMs, embeddings, transformers); experience applying AI/ML methods to real problems.
Communication: Ability to explain complex concepts clearly and patiently, adapting to match individual learning needs
Technical versatility: Comfortable learning new tools, technologies, and working across the data stack
Version control: Proficiency with Git/GitHub for collaboration and code management
Preferred Qualifications: 8-10+ years of experience and/or an advanced degree in data science, engineering, analytics, AI, or related role
Experience in civic technology, nonprofit organizations, philanthropy, or government
Exposure to working with vector databases, embeddings, or modern document stores
Experience integrating structured and unstructured data for analysis
Familiarity with responsible AI, model evaluation, and human-in-the-loop workflows
Experience building web-based data products or interactive applications (dashboards, data explorers, mapping tools)
Experience providing technical assistance or data capacity support to external partners
Experience strengthening data ecosystems or collaborative data infrastructure across multiple organizations
Knowledge of data governance, privacy, and ethics frameworks
Personal Qualifications: Demonstrated ability to work as part of a team and with people who hold diverse perspectives
Highly developed emotional intelligence and demonstrated ability to use interpersonal skills and political acumen in respectful and collaborative ways
Flexibility, commitment to teamwork, curiosity, and a sense of humor
Capacity to work amicably in a small office with high volume of work, as well as a deep sense of responsibility and accountability
Ability to make decisions, justify recommendations and be responsible and clear with stakeholders
A record of recognizing and acting on opportunities to continuously improve
High degree of professional ethics and integrity
Ability to work autonomously.
Benefits
RLD Foundation maintains a hybrid work environment where employees are expected to work in the office three days a week with occasional additional days as necessary.
Data Manager managing data analytics consulting projects at PwC. Collaborating on data - driven solutions and overseeing implementation while maintaining client relationships.
Principal Data Science Engineer at Qodea leading development of AI - driven reasoning tools and recommendation systems. Collaborating to bridge advanced analytics with practical implementation in Buenos Aires.
Lead Data Scientist at Target developing predictive and prescriptive algorithms for supply chain optimization. Collaborating across teams to foster data - driven decision - making while ensuring continuous innovation.
Data Scientist working with data analytics to drive efficiency improvements in the energy sector. Collaborate with teams to build and deploy models for actionable insights.
Senior Data Scientist at Betclic developing data products and user experiences in an innovative gaming environment. Collaborating across teams to drive data - driven decisions and product improvements.
Senior Data Science Engineer developing and maintaining machine learning models for fintech company. Collaborating with cross - functional teams to drive product improvements and user insights.
Senior Manager of Data Analytics leading high - impact analytics projects for business strategy at Conduent. Overseeing teams to develop data models and present insights to leadership.
Team Lead for Data Science at PAIR Finance focusing on machine learning product development. Leading a team to innovate in debt collection with AI - driven insights.