Data Analyst – Eliot-Pearson Department of Child Study & Human Development – (20001291)
This is a limited term position for 1 year with the possibility of renewal annually with continued funding and successful performance. This is a grant funded position and is not eligible for severance pay.
The Tufts Interdisciplinary Evaluation Research (TIER) group, housed within the Eliot-Pearson Department of Child Study and Human Development at Tufts University is seeking a Data Analyst (.8 to 1 FTE).
TIER is committed to conducting high-quality, collaborative evaluation research aimed at improving policies and programs for children, families, and communities. TIER conducts a range of mixed methods evaluations for family support programs across Massachusetts and other locales
The Data Analyst should be skilled in qualitative data collection and analysis, including participatory research approaches with a range of program stakeholders (e.g., participants, program staff, administrators, and funders); quantitative data collection and descriptive analysis; cleaning and analyzing program data; and writing and disseminating results for multiple audiences. The position will work on several family support evaluations, for example an evaluation of a place-based, multi-service family support program; a systems-level evaluation of a state-led initiative to support community responses to opioid use disorder; and an implementation evaluation of a collaborative community initiative to prevent child maltreatment.
Master’s degree in policy, social science, or related field, or Bachelor’s degree with at least five years strong experience.
Experience with qualitative data analysis software (e.g., NVivo, Dedoose).
Experience conducting focus groups and interviews.
Experience designing and programming online surveys (e.g., Qualtrics).
Ability to organize and summarize information in a clear and concise manner.
Knowledge of various evaluation designs and experience managing evaluations.
Ability to manage databases, construct data files, conduct and supervise data entry, and perform data edits/cleaning in a statistical software package (e.g., SPSS, Stata, SAS, R).
Knowledge of methods for protecting confidential data.
Expertise in using Microsoft Office software (i.e., Word, Excel, PowerPoint) and referencing software (e.g., Endnote, Zotero).
Experience in data quality control.
Experience conducting literature reviews.
Strong commitment to issues of equity and social justice.
Ability to work collaboratively with a multidisciplinary research team, yet feel comfortable making decisions independently.
High level of motivation, strong organizational skills, attention to detail, and effective communication skills.
Strong writing skills and ability to prepare clear documentation.
Exhibits intellectual independence and takes initiative.
Strong analytical skills.
An employee in this position must complete all appropriate background checks at the time of hire, promotion, or transfer.
Equal Opportunity Employer – minority/females/veterans/disability/sexual orientation/gender identity.