Title: Associate Data Scientist
Location: Local remote out of NYC (remote with occasional onsites)
Duration: 6-month contract-to-hire
Start Date: ASAP
The Associate Data Scientist will work in collaboration with senior data scientists, data engineers and data analysts to help equip communities and change agents with data and analysis tools. This individual will support a team to create new data sets, produce novel analyses, advise public, private, and non-profit sector partners, and integrate existing data sets to the platform to empower nonpartisan, evidence-based decisions. Our ideal candidate will have a keen interest in social and economic policy issues and the role of data in advancing racial equity. We will look for a demonstrated commitment towards wealth equity.
Responsibilities:
- Champion the responsible use of data and analysis – fairness, accountability, and transparency - in the mission of advancing wealth equity
- Collaborate with a team of at 1-3 data engineers and analysts, in research, design, implementation, and deployment of full-stack scalable data analytics to address challenging issues regarding wealth
- Support quantitative analysis on data to support creation of racial wealth equity insights
- Clean and format data for analysis and manipulation
- Ensure adoption of best-in-class processes and techniques for statistical analyses and modeling
- Assist in authoring papers, blogs, visualizations, and other dissemination materials
- Work with technical stakeholders and clearly translate and communicate complex concepts for non-technical audiences
Qualifications
- 1-2 years of experience in Data Science, Computer Science, Mathematics, Statistics, Economics, Public Policy, or a related field
- Experience or familiarity conducting analysis of economic data is preferred
- Experience navigating and managing deadlines in a high-volume, high-pace data collection industry, government, or academia
- Working knowledge of agile development methodologies
- Working knowledge of AI and machine learning algorithms including forecasting
Technical Expertise
- Demonstrated proficiency working with data collection, processing, and analysis in Python, R, GeoPandas, NumPy, Seaborn, or Scikit-Learn
- Practical knowledge of ETL processes to manipulate, clean and transform messy data with the aim of process automation
- Proficiency in SQL
- Experience with cloud computing technologies, big data platforms
- Experience applying data science methods (e.g., machine learning, natural language processing, imputations and time series analysis)
- Familiarity in modern data engineering tools and architectures such as BigQuery, AirFlow, Airflow, dbt, and Astronomer