Research Assistant Job at ACL Digital, Cambridge, MA

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  • ACL Digital
  • Cambridge, MA

Job Description

Title: Research Assistant

Duration: 06 Months with Possibilities of Extension

Location: Boston / Cambridge, MA 02138

The Corporate Net-Zero Emission Targets Project, with support from the Salata Institute for Climate and Sustainability, is seeking Research Assistants (RAs). In this project, faculty and researchers at the Client Place are evaluating voluntary corporate goals to reduce greenhouse gas emissions. For these Research Assistant (RA) positions, the tasks will focus on collecting data from firms’ sustainability reports, which will include tracking and reviewing reports, analyzing their carbon commitment statements, and converting this information into structured data.

Project Description

This project examines the surge of corporate net-zero and greenhouse gas emissions reduction targets to determine their effectiveness in achieving real emissions reductions, a critical step for meeting U.S. climate commitments. Led by a cross-disciplinary team supported by the Salata Institute for Climate and Sustainability at University, the research analyses how corporate pledges influence behaviour, decision-making, and environmental outcomes. The team is investigating the actions corporations take in response to net-zero commitments, comparing the behaviour of companies with and without targets, and identifying gaps in implementation. By exploring the legal, regulatory, and business drivers behind these commitments, the project aims to uncover challenges, unintended consequences, and opportunities to strengthen corporate strategies and regulatory frameworks, ultimately driving meaningful emissions reductions.

Job Description

  • The primary responsibility of Research Assistants is to review and analyze firms’ sustainability reports, focusing on their carbon commitment statements, and transform this information into structured, high-quality data. This role involves:
  • Tracking and reading sustainability reports from various firms.
  • Analyzing qualitative content, including carbon commitment statements and other environmental goals.
  • Codifying qualitative data into structured datasets in Excel.
  • Ensuring accuracy, consistency, and reliability of the collected data to support the project’s empirical research.
  • The position requires close attention to detail, an ability to follow instructions precisely, and the discretion to exercise sound judgment when interpreting ambiguous or nuanced statements. Ideal candidates will excel in a role that demands both meticulousness and independent thinking.
  • This position requires a minimum weekly commitment of 35 hours. The start date for this role will be in February 2025.

Preferred Qualifications

  • Bachelor’s degree in Statistics, Economics, Business, Environmental Management, and other related degree;
  • Basic understanding of economics, business concepts, and sustainability practices is strongly encouraged.
  • Prior experience in data collection, data entry, qualitative coding, and data entry is strongly desirable.

Skills:

  • Strong reading comprehension skills to carefully review and interpret detailed reports, identify key information, and synthesize content effectively.
  • Ability to process large volumes of qualitative information and quickly pinpoint relevant data.
  • Proficiency in Microsoft Office Suite, especially Excel; familiarity with statistical tools is a plus.
  • Strong organizational and time-management skills to handle multiple projects effectively.
  • Excellent communication and interpersonal skills to collaborate with team members and faculty.
  • High attention to detail and ability to ensure accuracy and reliability in data collection and entry.
  • Ability to work independently, manage tasks, and make informed decisions when dealing with complex or unclear information.
  • Commitment to meeting deadlines and delivering high-quality work.
  • A strong work ethic and a commitment to the project’s goals and timelines ensure that the data collection process moves smoothly and efficiently.

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