(Senior) Data Scientist
- Compensation
- Not disclosed
- Location
- DC, US
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Full time
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- A bachelor’s degree in economics, finance, math, computer science, data science, or a related discipline;
- Proficiency in Python, R, or Stata and demonstrated ability to learn and work in additional analytical languages;
- Strong SQL skills and experience designing and maintaining relational and analytical data systems, using tools such as PostgreSQL, DuckDB, or comparable technologies;
- Experience with data visualization and geospatial tools, such as Tableau, PostGIS, QGIS, Mapbox, ggplot2, or Matplotlib;
- Experience using various AI models to accelerate data collection and analysis;
- Knowledge of version control systems such as Git and GitHub and other quality control protocols;
- Strong communication, organizational, and problem-solving skills;
- The ability to work effectively in a fast-paced, team-oriented environment; and
- High initiative.
Nice to have
- A master’s degree in economics, finance, math, computer science, or a related discipline;
- Working experience with Stata and Microsoft Excel;
- Experience with web development, cloud-based, and development tools, such as HTML, JavaScript, AWS, or Docker;
- Experience automating, scheduling, testing, and documenting recurring data workflows, using tools such as Airflow, GitHub Actions, or comparable systems;
- A demonstrated interest in housing and public policy research;
- Experience managing other team members’ workflows; and
- A demonstrated track record of project management on data-management projects.
Full description
Overview
The Housing Center at the American Enterprise Institute (AEI) is the nation’s leading market-oriented housing research center. It operates at the intersection of data-driven housing knowledge and policy solutions.
The AEI Housing Center seeks a full-time, in-person (senior) data scientist to develop and manage large datasets to derive insights and inform US housing policy. The data scientist will be responsible for maintaining the nation’s foremost housing database and designing the systems and infrastructure that produce research to improve the operation of housing markets, mortgage lending practices, and housing policy. This will include seeking, creating, cleaning, and analyzing new datasets; developing automated processes for data maintenance; and building the infrastructure for regular Housing Center updates on the housing market.
This position requires superior technical and quantitative skills, the capacity to develop additional skills, and the initiative to build new systems and processes. The ideal candidate will have a demonstrated interest in and knowledge of housing policy. Creativity, attention to detail, and the ability to independently manage multiple complex projects and deliver reliable results are essential. The anticipated start date for this position is as soon as possible.
Final title and salary will be commensurate with a candidate’s educational level and years of full-time, applicable work experience. Master’s degree preferred. Candidates who can successfully meet the responsibilities of this role are encouraged to apply, regardless of their years of experience. AEI offers a stimulating and harmonious work environment and excellent benefits. Applicants must submit a cover letter demonstrating their interest in housing policy and noting their quantitative and technical experience and skills, a resume, an unofficial academic transcript, and a writing sample with the online application. Candidates also will be asked to pass a skills assessment and an analytical assessment.
Responsibilities
- Assemble financial, workforce, technological, economic, statistical, and other operational datasets to inform comparative and predictive analyses of housing issues.
- Develop models, algorithms, and metrics to facilitate data interpretation and work with team members to present and operationalize data for analysis.
- Automate recurring analyses that are currently performed manually, including data collection, cleaning, reporting, and visualization.
- Lead data projects from source acquisition through technical design, quality control, publication, and ongoing maintenance.
- Translate technical findings by creating interactive dashboards and data visualizations that make Housing Center data and insights accessible to researchers and the public.