Research Associate - Boston, United States - Harvard University

Harvard University Boston, United States

3 weeks ago

Description

Basic Qualifications

Basic Qualifications:

Advanced degree, or bachelor's degree, with 5+ years of relevant work experience required
Strong knowledge of machine learning techniques and statistical methods for data analysis and inference.
Proficiency in R (preferred) or Python.
Expertise in data visualization tools and techniques.
Experience working with large datasets and data manipulation.
Experience managing others and successfully working as part of a team.

Additional Information

This is a full-time term appointment starting this summer through June 30, 2025, with potential for re-appointment for the following year.

All HBS RA roles are structured as one-year appointments.

This role is offered as a hybrid (some combination of onsite and remote) where you are required to be onsite at our Boston, MA based campus 2-4 days per week.

Specific days and schedule will be determined between you and your manager. Candidates should expect to be on campus to support with course delivery in the Fall and Spring.

We may conduct candidate interviews virtually (phone and/or via Zoom) and/or in-person for this role.

A cover letter is required to be considered for this opportunity. All candidates will be expected to submit a writing sample, transcript, and a code sample.

Harvard Business School will not offer visa sponsorship for this opportunity.

Culture of Inclusion:

The work and well-being of HBS is profoundly strengthened by the diversity of our network and our differences in background, culture, national origin, religion, sexual orientation, and life experiences.

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Position Description

The Crafting Your Life (LIFE) project, led by Professor Leslie Perlow, is seeking a Research Associate - (Senior Data Scientist and Project Manager).

The mission of the LIFE project is to use technology to create new ways to collect data to simultaneously enable the study of what it means to live a well lived, while also providing users valuable insights that make a difference in how they live their own lives.

Professor Perlow and the LIFE project are seeking an experienced data scientist to help them make the most of this exciting opportunity

The project:
1) has resources to design and build its own data collection tools, 2) has access to ongoing - and potentially longitudinal - quantitative data on tens of thousands of users, and 3) consists of an interdisciplinary group of researchers and practitioners interested in exploring these topics.

In particular, Professor Perlow and the LIFE project are seeking a data scientist with expertise in quantitative data analysis and data analytics to help lead the data collection and analysis.

They seek a candidate who has completed their master's in data science (or a related field) to partake in the design and management of multiple quantitative data collection efforts.

The successful candidate will be eager to creatively design data collection efforts, analyze resulting data, and manage the team. The data analysis will involve data from existing tools that have already been developed for this special project (e.g. LIFE Simulation, LIFE Connect, Developmental Relationship Mapping), but most importantly center around the flagship tool in development - the LIFE Matrix.

This new tool, with an MVP planned to release in September 2024, explores how users spend their time and the value those time allocations bring to them as well as provides users insights and recommendations based on comparing them with others like themselves.

The ideal candidate will act as a collaborator, thought partner, and leader for the project. They will be involved in doing sophisticated data analysis and data visualization. They will provide advanced subject-area expertise, analysis, and interpretation.

They will also play a central role in overseeing the project's work with faculty, executive fellows, doctoral students, and research associates, and helping to manage the project's day-to-day activities.

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