Data & ML Product Intern

Prácticas(de 4 a 6 meses)
Paris
Salario: ≥ 1,5K € por mes
Fecha de inicio: 01 de septiembre de 2024
Unos días en casa
Experiencia: < 6 meses
Formación: Licenciatura / Máster

Monk AI
Monk AI

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El puesto

Descripción del puesto

Missions:

As a ML/data intern you will be joining the Monk Product and Business Team. Your missions will be :

  • Contribute to the prototyping of state-of-the-art damage detection approaches (multi-modality, proprietary datasets, adequate computing power,…)

  • Shape pitches, write specifications (user stories) for new features, or to improve existing ones

  • Work closely in a technical environment to frame, investigate and validate new features • Partner with all the Feature team’s stakeholders to ensure perfect alignment on problems to solve and how.

  • Work closely with business team and product team to make data driven analysis on core processes (data labelling, data capture, data ingestion…)

  • Build dashboard for C-level executives

  • Explore new product opportunities (Gen AI, multimodality, capture devices, automation…)


Requisitos

Tech stack:

  • Databases: SQL, BigQuery

  • Languages: Python

  • ML (appreciated): Pytorch

Skills:

  • Technical knowledge in Python, API and dashboard.

  • Ability to manipulate large data volumes and produce efficient transformations.

  • Experience delivering complex projects involving scientists and engineers within tight time frames while meeting quality and cost targets.

  • Strong analytical and problem solving mindset.

  • Organizational and project management skills as well as the ability to multitask on various projects in a fast-paced environment.

  • Excellent written and verbal communication skills.

  • Fluency in spoken and written English.

Background:

  • Currently pursuing a Master’s Degree in Engineering with IT courses

  • Experience working in an enterprise technology setting (appreciated)


Proceso de selección

Interview process:

  • Meet interview (30min)

  • Technical Interview + Test (1h)

  • Data product case + restitution (1h)

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