Data Scientist (Recommender Systems)

Frontiers + Seguir empresa
100% En remoto 10/08/2022

Descripción de la oferta de empleo

We are on a mission to make science open so everyone can live healthy lives on a healthy planet

Who we are

Frontiers is an award-winning open science platform and leading open access scholarly publisher.

We are one of the largest and most cited publishers globally. To date, our 200,000 freely available research articles have received more than 1 billion views and downloads and 2 million citations. Our journals span science, health, humanities and social sciences, engineering, and sustainability. And we continue to expand into new academic disciplines so more researchers can publish open access.

Be part of the publishing revolution and help us transform the way research is published, evaluated, and communicated to the world.

Job Role

We are looking for a Recommender Systems Data Scientist who can work on production-ready Artificial Intelligence (AI) to support our industry-leading AI publishing platform.

You will work in a product-focused team of Data Scientists working collaboratively as part of a larger AI department to develop cutting edge solutions that will evolve our state-of-the-art AI Review Assistant (AIRA)

Key Responsibilities

- Development, optimization and evaluation of ML models and algorithms

- Technological review of data science solutions and communication to non-technical stakeholders

- Proactive identification of opportunities for potential AI products within Frontiers

- Effective collaboration with Product Managers, ML Engineers, Software and Data Engineers to design scalable state of the art ML models


- Solid experience of working as a Data Scientist (ideally in a commercial setting)

- Familiarity with: Topic modelling, content embedding, collaborative filtering, vectorization, KNN models, evaluating recommender systems

- Proficiency in Python

- Willingness to share and adopt best work practices on a common codebase (Python packaging, version control, pull requests, testing, continuous integration)

- Experience with SQL and big data platforms (e.g. Spark, Azure Databricks)

- Familiarity with problem specification formulation and translation to functional/non-functional requirements for ML model building

- Familiarity with identifying under/over fitting in ML models and bias/variance trade-offs

- Familiarity with algorithm selection giving consideration to accuracy, training time, model complexity, parameters´ and features´ management


With more than 50 nationalities represented in our global team, you will work regularly with teammates in other countries, and with our community of researchers, editors, and authors from around the globe.

Our mission to create solutions for healthy lives also extends to the working environment we provide for our employees.

This includes:

- 100% remote working
Employees now have the flexibility to choose where they want to work, with remote working available on a part- or full-time basis.

- Learning and development
All employees have access to LinkedIn Learning (and Pluralsight for our technology team), an annual personal learning budget, and dedicated L&D time.

- Wellbeing
We offer free online yoga classes, an employee assistance plan, access to the Headspace app, and four wellbeing days on top of your annual leave allowance.

- Volunteering opportunities
Employees can dedicate three days each year to volunteer for a personal cause or through our volunteering partner platform, Alaya.

Frontiers actively embraces diversity and is a safe and welcoming workplace. Recruitment is free from discrimination – including based on race, national or ethnic origin, age, religion, disability, sex, gender identity or sexual orientation. With over 600 employees from more than 50 different nations, our diversity creates vibrant teams and constantly challenges us to appreciate multiple perspectives.

Otros detalles de la oferta

Formación Mínima: Grado Medio

Nivel Profesional: Empleado

CVs inscritos en el proceso: 64

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Datos principales de la oferta
  • 100% En remoto
  • Big Data
  • Jornada completa
  • 1 año
  • Indefinido
    Tipo contrato
  • python

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