Senior Data Scientist (AI)

TL;DR

Senior Data Scientist (AI): Designing, training, and evaluating machine learning models for bidding, forecasting, and outcome optimization within a streaming and CTV advertising platform with an accent on A/B testing, feature engineering, and productionizing models. Focus on collaborating with MLOps and Data Engineering teams to deploy scalable solutions on Vertex AI and translating complex model behaviors into actionable business insights.

Location: Must be based in the European Union region and possess a valid work permit.

Company

hirify.global is a global AI-first digital transformation and engineering partner with over 25 years of experience, delivering data-driven solutions for major international clients.

What you will do

• Design, train, and evaluate models for bidding, forecasting, and targeting.
• Design and analyze A/B tests and online experiments to connect model performance to revenue.
• Transform raw campaign and audience data into robust, reusable features for a shared feature store.
• Collaborate with MLOps and Data Engineering teams to deploy models into production on Vertex AI.
• Frame problems and communicate model impact to product owners and business stakeholders.

Requirements

• Must be based in the European Union region with a valid work permit.
• Proven experience applying machine learning to real-world products with a track record of successful deployments.
• Strong proficiency in Python and SQL.
• Fluency in modern ML stacks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Solid grounding in statistics, experimentation, and A/B testing methodologies.
• Experience with large-scale data and cloud ML tooling, specifically Google Cloud and Vertex AI.

Nice to have

• Background in adtech, real-time bidding, recommender systems, or marketing science.
• Experience with feature stores and MLOps pipelines.
• Ability to transition from ad-hoc notebooks to reproducible workflows.

Culture & Benefits

• Focus on engineering excellence and a people-first culture.
• Opportunities to work with leading technologies like Databricks and Snowflake.
• Strong emphasis on continuous growth and knowledge sharing.
• Exposure to high-profile international clients across various industries.

Hiring process

• CV review
• HR call
• Interview
• Client interview
• Decision