129 Church Street
DATA ANALYST/RESEARCH ASSOCIATE
New Haven, Connecticut
Post Date 10/29/2018 - Open Until Filled
DataHaven is a non-profit 501(c)3 organization that directly supports hundreds of community, academic, government, philanthropic, and health care organizations by collecting, interpreting, and sharing high-quality public information. With a 25-year-history of public service in Connecticut communities, DataHaven is a formal affiliate of the National Neighborhood Indicators Partnership (NNIP), a collaborative national effort by the Urban Institute and local partners to further the development and use of neighborhood information systems in local policymaking and community building.
The Data Analyst/Research Associate is a full‐time or part-time position based in downtown New Haven, Connecticut. Adding to our diverse team of researchers and project staff, the Data Analyst/Research Associate will collect and analyze Connecticut town and neighborhood-level data pertaining to demographics, public health, economics, and quality of life. The ideal candidate will enjoy working with a range of research techniques to answer questions about social and economic well-being in our communities, and to communicate these issues to a broad audience.
● Love of data, and a curiosity or experience in applying public data to improve well-being and social justice, especially within historically oppressed communities and in public policy-making;
● A bachelor’s degree and strong quantitative analysis skills, preferably in statistics, social science, community and economic development, public health, epidemiology, and/or related fields;
● At least 1 year of work experience organizing, processing, and analyzing data, including writing programs or scripts through the use of at least one statistical or mathematical software package or language (e.g. R, Python, SPSS, or similar), and a rigorous attention to detail;
● Ability to write about data to describe patterns and trends to general, non-technical audiences;
● Ability to work both independently and collaboratively with a diverse team on multiple projects in a fast-paced, dynamic environment and within tight timeframes, with high capacity for self-motivation, self-learning, and meeting deadlines.
● Experience using open source version control, preferably Github or similar project tools;
● Experience working with raw data from large-scale, high-quality national or statewide surveys or other large data sets to develop and apply spatial, multi-level and longitudinal analysis methods using statistical and/or GIS software, in a form suitable for public dissemination;
● An advanced degree, or the equivalent combination of training or experience.
DataHaven is an equal opportunity employer. We do not and will not discriminate in employment and personnel practices on the basis of race, sex, age, handicap, religion, national origin or any other basis prohibited by applicable law. Hiring, transferring and promotion practices are performed without regard to the above listed items. We commit to affirming the value of diversity and promoting an environment free of discrimination.
ADDITIONAL INFORMATION AND BENEFITS
● Work schedule, start date, and term of service to be negotiated. Salary range is $45K to $75K and to be determined based on experience.
● Sixth-floor downtown office overlooking City Hall, Yale University, and New Haven’s beautiful public square. New Haven is one of the nation’s most walkable cities, and is located 60 miles from New York City and 130 miles from Boston.
● Help change public policy and improve your community.
Minimum Education Required
How To Apply
Please submit your cover letter and resume, via email to info (at) ctdatahaven.org, or via mail to 129 Church St, Suite 605, New Haven, CT 06510. Due to our small staff size, we are unable to respond to inquiries about this position, and phone calls will not be accepted. The cover letter should explain your interest in the position and describe your relevant experience, and describe your potential availability and/or preferred start date.