Data Scientist, Ad-Tech (Remote) – Global Impact

Lever, Inc.; Lavamünd; Vor Ort; EUR 148.000 - 201.000; Vollzeit

Benefits dieser Stelle

Direct exposure to founders and impact

Learning and development budgets

Remote work with flexible schedule

Office relocation option to Berlin

Home-office setup budget

Global team across Europe, Asia, North

Annual learning budget

Large-scale ML systems experience

Collaborative international culture

Zusammenfassung

Lever, Inc. is seeking a Data Scientist to work on large-scale machine-learning models that process terabytes of data to support billions of real-time advertising requests.

You will contribute across the full data science lifecycle, from research and experimentation to production deployment, collaborating with ML engineers, analysts, and other data scientists. The role emphasizes experimentation, feature engineering, and scalable solutions with measurable business impact, in a diverse, globally

Qualifikationen

• 3+ years of experience building data science products from research to production.
• Proficient in Python, Spark, Hadoop, Airflow, Docker and SQL.
• Ad-Tech experience is required.
• Experience with ML models for sparse and large-scale data.
• Experience with neural networks for classification, regression, or multitask learning is valuable.

Aufgaben

• Develop, improve and deploy data science products across the full lifecycle.
• Enhance models with new features and data sources.
• Collaborate with ML engineers, analysts and data scientists.
• Design, run and evaluate A/B tests to guide decisions.
• Build dashboards and SQL tools to monitor model performance.

Kenntnisse

Python

Spark

Hadoop

Airflow

Docker

SQL

Tools

CatBoost

LightGBM

Jobbeschreibung

Lever, Inc. is seeking a Data Scientist to work on large-scale machine-learning models that process terabytes of data to support billions of real-time advertising requests.

You will contribute across the full data science lifecycle, from research and experimentation to production deployment, collaborating with ML engineers, analysts, and other data scientists. The role emphasizes experimentation, feature engineering, and scalable solutions with measurable business impact, in a diverse, globally