Skills

Communication Research Machine Learning Analytical Skills Analytics Data Science

Job Specifications

Company Description

Company Description

Daice Labs is building hybrid AI frameworks that integrate today's models into systems that learn continuously. Founded by MIT CSAIL scientists, we focus on building new architectures by combining LLMs/DL with symbolic reasoning and bio-inspired system design. Operating on two tracks, our Product Lab develops industry-specific solutions for collaborative human teams + AI co-building and co-owning vertical applications, while our Research Lab explores how principles of natural intelligence can guide systems design of new hybrid AI architectures.

Join us in taking the next leap in productivity through collaborative innovation.

Role Description

This is a full-time remote role for a Data Analyst within our R&D team. The Data Analyst will be responsible for analyzing complex datasets, developing data models, and applying statistical techniques to uncover insights. Day-to-day tasks will include collecting, cleaning, and interpreting data, as well as communicating findings to stakeholders. As part of our dynamic team, the Data Analyst will contribute to advancing our understanding of how natural intelligence principles can inform AI design.

Qualifications

Strong Analytical Skills and Data Analytics experience
Proficiency in Statistics and Data Modeling
Excellent Communication skills to convey complex findings clearly
Ability to work independently and as part of a remote team
Experience with AI and machine learning frameworks is a plus
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field

About the Company

Daice Labs -- Digital co-builders engineering adaptation The Problem Current AI shines on benchmarks but breaks in the wild--brittle under distribution shift, costly to retrain, hard to audit, and slow to adapt. The need? new hybrid paradigms that integrate today's models into systems that learn continuously, generalize, and explain their decisions. Approach Founded by MIT CSAIL scientists, we build hybrid/composite frameworks that combine LLMs/DL with symbolic reasoning and bio-inspired system design to deliver new architec... Know more