Senior Data Scientist

W speedapp wierzymy, że organizacja jest tak dobra jak tworzący ją ludzie. Jesteśmy zespołem ekspertów IT i innych specjalistów pracujących dla naszych klientów na całym świecie (m.in Izrael, Austria, USA). Wykraczamy daleko poza kategorię HR. Budujemy zespoły IT, a także pomagamy w ich zarządzaniu.

👉 10 lat doświadczenia

👉 +100 klientów na całym świecie 

+300 zatrudnień rocznie

💎 Jesteśmy laureatem prestiżowej nagrody Diamenty Forbes cztery lata z rzędu (2022, 2023, 2024, 2025), członkiem sieci Fast Growth Icons oraz FinTech Poland.

• Experience with neural networks and deep learning, including practical work on Deep Learning models in critical production applications.
• Proven experience on large-scale data sets.
• Proficiency in deep learning frameworks such as PyTorch or TensorFlow and strong knowledge of Pandas and NumPy.
• Advanced SQL skills, preferably analytical SQL in large-scale environments such as BigQuery.
• Experience with public cloud, preferably Google Cloud Platform, including ML services like Vertex AI and Vertex Pipelines.
• End-to-end model development experience from problem formulation and feature design through evaluation to production deployment.
• Solid engineering skills, producing production-level, testable code in Python with familiarity with CI/CD.
• Independence and decision-making readiness.
• Education or experience in STEM fields such as Computer Science, Mathematics, Statistics, Quantitative Methods, or Physics.
• English language proficiency at minimum B2 level.

Nice to have:

• Experience in digital advertising, retail media, ad-tech, or marketplace.
• Familiarity with modeling CTR and CVR (click and conversion prediction).
• Experience with large-scale ranking or recommendation systems.
• Experience with online low-latency applications.
• Proficiency in classical ML techniques, e.g., Gradient Boosted Trees.
• Experience in mentoring or technical leadership.
• Practical usage of AI tools supporting coding.

• Designing, improving, and evaluating ML scoring models (CTR, CVR, RoAS) driving ad ranking and personalization in a high-throughput, low-latency environment.
• Developing modeling strategies integrating user, product, and placement signals across the platform.
• Collaborating with engineering teams and business stakeholders to translate strategic goals into measurable model outcomes and technical roadmaps.
• Providing technical leadership and quality control for Data Science work according to production standards.
• Supporting the development of other Data Scientists.
• Working with large-scale data in an international environment with English communication.