Senior Data Scientist

Jobgether SRL; Italia; In loco; EUR 75.000 - 110.000; Tempo pieno

Vantaggi offerti da questo lavoro

Flexible work-from-home

Relocation to international office

Learning & development budget

Home-office setup budget

Descrizione del lavoro

Jobgether SRL, on behalf of a partner company, is seeking a Senior Data Scientist based in Italy. The role focuses on developing and deploying machine learning products at global scale, handling billions of ad requests in real time.

You will collaborate with ML engineers, data scientists, and analysts to deliver measurable business impact across a global platform. Requirements include 5+ years in data science or ML, strong Python/Spark/Hadoop/Airflow/SQL skills, and experience with sparse,

Competenze

• At least 5 years of professional experience developing data science or machine learning products.

Mansioni

• Develop, enhance, and optimize ML models for large-scale data.

Conoscenze

Python

Spark

Hadoop

Airflow

SQL

Reinforcement learning

Model deployment

Experimentation

Strumenti

Docker

Descrizione del lavoro

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Scientist based in Italy. As a Senior Data Scientist, you’ll develop and improve machine learning products operating at exceptional global scale. You’ll work with large, complex datasets and models that process billions of ad requests and users in real time. The role spans the full data science lifecycle, from research and experimentation through production deployment and optimization. You’ll collaborate closely with data scientists, analysts, and machine learning engineers to build scalable solutions with measurable business impact. Your work will help optimize customer acquisition, retargeting, and advertising performance across a global technology platform. You’ll have significant opportunities to experiment with new algorithms, data sources, and modeling approaches. Joining a distributed, international team, you’ll contribute to a fast-moving environment focused on innovation, collaboration, and continuous learning.

Accountabilities

• Develop, enhance, and optimize machine learning models by introducing new features, tuning parameters, and incorporating additional data sources.
• Collaborate with Machine Learning Engineers to research, develop, and deploy scalable supervised and unsupervised learning algorithms.
• Explore new and existing data sources to identify opportunities for improving model performance and creating new data-driven solutions.
• Research and evaluate innovative machine learning approaches that can optimize different stages of the product and advertising value chain.
• Design, run, and analyze A/B tests to validate hypotheses, measure impact, and continuously improve models and strategies.
• Develop solutions capable of handling sparse, high-volume datasets for use cases such as prediction, clustering, and outlier detection.
• Contribute to neural-network-based products supporting classification, regression, and multi-task learning.
• Build clean, reproducible, and well-tested code that can reliably move from research environments into production.
• Develop and improve monitoring tools and dashboards to track model and system performance.
• Work collaboratively with analysts, engineers, and other data scientists to translate business and product challenges into practical machine learning solutions.
• Apply an experimentation-driven, impact-focused approach, prioritizing simple and effective solutions over unnecessary complexity.

Requirements

• At least 5 years of professional experience developing data science or machine learning products, from initial research through production deployment.
• Strong programming skills and a commitment to writing clean, maintainable, reproducible, and well-tested code.
• Strong hands-on experience with Python, Spark, Hadoop, Airflow, Docker, and SQL.
• Proven experience working with algorithms designed for sparse and large-scale datasets, including prediction, clustering, and outlier detection.
• Practical experience developing neural network-based solutions for classification, regression, multi-task learning, or related applications is highly valuable.
• Knowledge of reinforcement learning and large-scale optimization is a significant advantage.
• Good understanding of SQL and dashboards for developing, monitoring, and improving data science and machine learning systems.
• Strong communication and collaboration skills, with the ability to work effectively alongside data scientists, analysts, and engineering teams.
• A pragmatic, experimentation-oriented mindset and the ability to focus machine learning work on measurable product and business outcomes.
• Previous professional experience in AdTech is required, ideally including exposure to mobile app advertising technology.

Benefits

• Direct collaboration with founders and the opportunity to make a meaningful impact on products and business direction.
• Strong opportunities for career development, learning, and professional growth.
• The chance to work alongside experienced industry specialists and entrepreneurs in a rapidly evolving technology sector.
• A diverse, multinational, and distributed team working across Europe, North America, Asia, and other regions.
• Flexible work-from-home arrangements.
• Opportunity to relocate to an international office in Berlin.
• $500 home-office setup budget.
• $1,000 annual learning and development budget.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.