Intro

Adsquare's mission is centered on:

Passion: Solving complex challenges with exceptional people, technology, and data.
Niche: Specializing in Location Intelligence for Programmatic Advertisers.

Our work is guided by our core values, and we look for candidates who embody them:

Drive: Turning ambition into action that brings valuable outcomes.
Resilience: Adapting, persevering, and growing stronger through challenges.
No BS: Upholding honesty, transparency, and clear communication.
Humble: Valuing modesty and letting results speak for themselves.
Moral Compass: Acting with fairness, integrity, and respect.

Your Mission

As a Data Scientist at Adsquare, you will transform massive geospatial and behavioral datasets into production-ready intelligence. You won't just build models in a vacuum; you will collaborate with ML Engineers and Product owners to integrate advanced analytics into our core programmatic advertising platform. This role is a blend of high-scale engineering and rigorous scientific research.

Your Profile

Experience: 5+ years (B.S.), 3+ years (M.S.), or 1+ year (Ph.D.) in a hands-on Data Science role.
Theoretical Mastery: Strong foundation in Probability, Inferential Statistics, Linear Algebra, and Experimental Design.
Python Stack: Expert proficiency in pandas, scikit-learn, PyTorch/TensorFlow, and FastAPI.
Large-Scale Data: Proven experience querying and manipulating TB-scale datasets using SQL (e.g., BigQuery, Athena, Redshift, or Snowflake).
Cloud Production: Experience deploying and monitoring models within AWS (SageMaker, Lambda) or similar cloud environments.

Educational Background:

Bachelor’s or Master’s degree (Ph.D. is an advantage) in a relevant quantitative empirical science field (e.g., Mathematics, Physics, Statistics, Engineering, Machine Learning, Computer Science, Economics, Social Sciences, Psychology, Neuroscience) or equivalent practical experience.

Soft Skills & Personal Attributes:

A strong commitment to Adsquare's core values: Drive, Resilience, No BS, Being Humble, and a strong Moral Compass.
Exceptional written and verbal communication skills, with the ability to translate complex technical concepts into clear, actionable insights.
A proactive, research-driven approach to creatively and precisely solving complex challenges.

What you will do

End-to-End ML Development: Design, train, and deploy machine learning models at scale, focusing on location intelligence and audience attributes.
Production Excellence: Partner with Data/ML Engineers to ensure models are robust, monitored, and seamlessly integrated into our cloud-native production workflows.
Strategic R&D: Lead research initiatives involving LLMs (LangChain, MCPs, specialized agents) and classical statistical/ML modeling to solve complex spatial problems.
Data Advocacy: Conduct rigorous EDA and experiment design to ensure data quality and provide actionable insights for strategic decision-making.
Scientific Contribution: Represent Adsquare by contributing to peer-reviewed publications and staying at the forefront of spatial data science.

Nice to Have

Data Modeling: Experience with dbt and modern data stack orchestration.
Generative AI: Hands-on experience building LLM-based applications using e.g., LangChain, MCPs, Streamlit.
Domain Expertise: Prior experience in Programmatic Advertising or Geospatial/GIS data.

Our Software Stack

Languages: Python, SQL
Tools: AWS (SageMaker, Redshift, Athena), Snowflake, dbt, FastAPI, Docker
ML/AI: PyTorch, Scikit-learn, LangChain, Streamlit

Why us?

On top of a competitive package…

We are open to flexible work models: we work on a hybrid mode and remotely from anywhere in the world up to 3 months per year
To encourage education and professional growth, we offer an individual yearly budget of 1.200€
You are entitled to 30 vacation days per year
We offer Urban Sports Club membership, company pension scheme
Regular team events and company events organised by our People team (Trust us, they know how to throw a party!)
We equip you with the latest hardware and provide you with all the tools you need to thrive

Salary Range (Annual On-Target Earnings)

60.000 - 70.000

Recruiting Process

could require on site steps

Step 1: Short 30-min take-home technical quiz.
Step 2: Value-based interview (30 mins).
Step 3: Deep-dive technical interview (1.5 hours) with the Data team.
Step 4: Practical data-crunching challenge.
Step 5: Team Meet & Greet — the final step to ensure we’re a great fit for each other.

Work model

Hybrid

Desired start date

Asap