Data Scientist

About the role

As a Data Scientist at ACC Group AG you will operate at the crossroads of artificial intelligence, finance and data infrastructure. You will build and maintain data pipelines that feed both the training of proprietary AI models and the real‑time inference systems used by our clients. The role involves curating high‑quality financial and market datasets and collaborating closely with AI research, backend and product teams.

Key responsibilities

• Design, implement and maintain robust data pipelines for training and production environments.
• Curate, preprocess and validate large‑scale financial, behavioral and market datasets for AI model development.
• Build data infrastructure that supports continuous learning, retraining and real‑time inference.
• Collaborate with AI engineers to design feature pipelines and model input structures for supervised and unsupervised learning.
• Monitor data integrity, consistency and performance across ingestion and storage layers.
• Develop data governance frameworks ensuring traceability, auditability and compliance with FINMA, GDPR and FADP standards.
• Optimize ETL and ELT processes for efficiency and scalability in multi‑cloud environments.
• Create analytical dashboards and metrics for tracking data quality, model performance and business KPIs.
• Work with backend engineers to deploy data services that integrate seamlessly with production systems.
• Identify opportunities for automation and optimization throughout the data lifecycle.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics or a related technical field, or equivalent professional experience.
• 3+ years of professional experience as a Data Scientist, Data Engineer or ML Engineer, preferably in fintech or technology‑driven environments.
• Fluent in English; German is an advantage.

Required skills

• Python (including Pandas, NumPy, PySpark).
• SQL.
• Data pipeline frameworks such as Airflow, Prefect or Luigi.
• Cloud platforms: AWS, Azure or GCP.
• Distributed processing tools: Spark, Databricks.
• MLOps and data versioning tools: MLflow, DVC or similar.
• Experience with real‑time market or transactional data feeds.
• Knowledge of data security, encryption and identity management in regulated environments.
• Understanding of FINMA, GDPR and FADP compliance requirements.