Data Scientist

Prime Insights; España; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Prime Insights, a Sweden-based technology company, is seeking a Data Scientist to build predictive models and recommendation systems to improve user engagement, LTV, and fraud detection in a high-scale product environment.

You will work within the Central Data Team to power an international community, leveraging Python and SQL to deliver advanced analytics, experimentation frameworks, and real-time systems.

Formación

• 3+ years of experience in Data Science, ideally within AdTech, Gaming, or FinTech.
• Expert proficiency in Python (Scikit-learn, XGBoost/LightGBM/CatBoost, PyTorch) and Advanced SQL.
• AdTech knowledge: CPM, ROAS, Attribution, Post-back loops.
• Strong communication skills to explain findings to technical and non-technical audiences.
• Experimental design: strong understanding of A/B testing in high-traffic environments.
• Product curiosity: understanding the psychology of user choices.

Responsabilidades

• Build predictive models and recommendation engines to maximise engagement.
• Develop LTV and churn models to optimise acquisition spend.
• Create real-time fraud and anomaly detection systems.
• Lead experimental design and analysis for robust insights.
• Move from descriptive to diagnostic and predictive analytics.

Conocimientos

Data Science

Python

Advanced SQL

A/B testing

AdTech knowledge

Communication

Experimental design

Product curiosity

Herramientas

Scikit-learn

XGBoost

LightGBM

CatBoost

PyTorch

Descripción del empleo

Prime Insights is a Sweden-based technology company reaching millions of diverse users through our proprietary Market Research Panel. Beyond our world-class Market Research Panel, we are scaling our Offerwall and Play-to-Earn (P2E) ecosystems. We connect millions of users to games and products they love, leveraging sophisticated targeting to ensure high engagement for advertisers and maximum rewards for our users.

As part of our Central Data Team, you will be the backbone of our intelligence, building the models and systems that power our international community.

We are looking for a Data Scientist who can build predictive models, recommendation systems, and experimentation frameworks to improve user engagement, LTV, and fraud detection in a high-scale product environment. Experience in AdTech, Gaming, or similar industries is a strong plus.

What You’ll Do

• Predictive Targeting & Personalization: Build recommendation engines that match the right offer (game/survey) to the right user at the right time to maximise user engagement.
• User Lifetime Value (LTV) Modeling: Develop models to predict long-term user value and churn, allowing us to optimize user acquisition spend.
• Fraud & Anomaly Detection: Guard the ecosystem by building real-time systems to detect "farming," bot behavior, and VPN spoofing.
• Statistical Rigor: Serve as the internal consultant for experimentation (A/B testing) design, ensuring results are statistically significant and unbiased.
• Advanced Analytics: Move beyond descriptive reporting into diagnostic and predictive analytics.

What We’re Looking For

• 3+ years of experience in Data Science, ideally within AdTech, Gaming, or FinTech.
• Core Tech Stack: Expert proficiency in Python (Scikit-learn, XGBoost/LightGBM/CatBoost, PyTorch) and Advanced SQL.
• AdTech Knowledge: Familiarity with concepts like CPM, ROAS, Attribution, and Post-back loops.
• Strong communication skills: Able to clearly explain findings, assumptions, and tradeoffs to both technical and non-technical audiences.
• Experimental Design: Deep understanding of A/B testing in high-traffic environments where "noise" is high.
• Product Curiosity: You don’t just build models; you want to understand the psychology of why a user clicks one game over another.

Important: We are not considering freelancers working on multiple projects simultaneously. This is a full-time position for a dedicated Data Scientist who is ready to commit to a single product ecosystem and contribute meaningfully to its long-term success.