TL;DR

Data Scientist (Machine Learning/AI): Building and improving personalisation, recommendation, and forecasting models with an accent on demand prediction, logistics optimization, and churn prediction. Focus on applying newer technologies like LLMs and generative AI in production and supporting core business outcomes.

Location: Remote within Portugal, with the option to join the Lisbon office for collaboration days.

Company

%hirify_global% is a food-tech company operating a global meal kit platform focused on making home cooking easy, joyful, and sustainable.

What you will do

Design, build, and improve personalisation and recommendation models for meal kits and content.
Develop and maintain forecasting and planning models for demand prediction, logistics, and food waste reduction.
Support retention and marketing initiatives with churn prediction, CLV modelling, and campaign optimisation.
Explore and apply LLMs and generative AI in partnership with product and engineering.
Design and analyse A/B tests and experiments to ensure evidence-backed decisions.
Work end-to-end on models from data exploration to deployment and performance monitoring.

Requirements

Around 3+ years of experience in applied data science or a similar role.
Solid knowledge of machine learning, statistics, and time-series modelling.
Proficiency in Python and SQL, and hands-on experience with common ML libraries (scikit-learn, PyTorch, XGBoost).
Experience working with modern data platforms (Snowflake, Looker, Airflow or similar tools).
A sense of ownership: you care about the quality, reliability, and impact of the solutions you deliver.
Ability to explain complex ideas in simple, clear language to non-technical stakeholders.

Nice to have

Experience in subscription, e-commerce, or consumer products businesses.
Previous work on personalisation, recommendations, or customer lifecycle topics.
Exposure to LLMs or generative AI in real product use cases.
Experience working in Agile, cross-functional product teams.

Culture & Benefits

The chance to work on meaningful problems that connect directly to how people cook and reduce food waste.
A supportive, cross-functional environment where data, product, and engineering work closely together.
Opportunities for learning and growth through feedback, experimentation, and exposure to different business areas.
A culture that values impact, collaboration, and sustainable ways of working.
Hybrid work policy with 22 annual leave days +2 days extra for every year of tenure (up to 6).
5 training days per year and private health insurance provided by Tranquilidade.
Food allowance of 7.62€/worked day under Coverflex and 24/7 confidential employee assistance program.

Data Scientist (Machine Learning)