Dicey Tech provides a platform that lets data professionals create project portfolios to showcase their real‑world skills, bypassing traditional experience‑based job filters. Using AI, it matches users with suitable roles and hackathons sponsored by top companies, while highlighting transferable abilities and connecting them to a community of tech peers.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional job platforms prioritize years of experience and generic resumes, causing data professionals’ project work and real‑world problem‑solving abilities to be overlooked. As a result, candidates struggle to demonstrate transferable skills and find roles that match their actual capabilities.
Solution
Dicey Tech provides an AI‑driven hiring platform that centers on skill‑based portfolios rather than traditional CV metrics. Users can create a single, dynamic portfolio that aggregates projects, hackathon contributions, and quantified skill data. The system analyzes the portfolio to surface transferable competencies and matches candidates with employers seeking those specific abilities. Real‑world hackathons sponsored by leading companies give users opportunities to showcase problem‑solving prowess in a verifiable context. Additionally, the platform offers a community space where data professionals can network, share knowledge, and receive career guidance.
Target Audience
Primary users are data scientists, analysts, and engineers seeking to showcase their project work and find skill‑aligned employment, as well as hiring teams looking to source talent based on proven competencies.
Features
- AI-powered skill extraction that converts project data into a structured competency profile
- Automated job matching that aligns candidates with roles based on demonstrated skills and interests
- Integrated hackathon platform allowing users to participate in sponsored challenges and add verified results to their portfolio
- Dynamic portfolio builder that updates skill scores as new projects are added, eliminating the need for multiple CV versions
- Community hub for peer networking, mentorship, and collaborative learning among data professionals