Data Scientist

Location

Basel, Switzerland

3 years, with possible extension

3+ years

Utilities & Energy (Energie & Wasserversorgung) or Telecommunications or Banking & Financial Services or Information Technology & Services

We are looking for an experienced Data Scientist to support a long-term enterprise project in Basel. This 3‑year contract role offers the possibility of extension and requires senior‑tier expertise to design, build, and optimize an enterprise‑wide data platform. The role focuses on breaking down operational data silos, constructing scalable, low‑latency ETL/ELT pipelines, and establishing a unified data architecture that delivers clean, highly structured, and reliable data streams for downstream business intelligence, advanced analytics, and AI initiatives.

• Problem Translation:
  Translate high‑level operational and business challenges into precise exploratory data science tasks, mathematical formulations, and algorithmic solution blueprints.
• Model Engineering Loop:
  Perform structured feature engineering, sample selection, model training, hyperparameter optimization, and statistical validation across diverse algorithm classes.
• Production Microservice Packaging:
  Wrap validated machine‑learning pipelines into secure, containerized microservices exposed via reliable APIs.
• Governance & Tracking:
  Establish model monitoring configurations to track feature drift, analyze concept decay, measure latency drops, and enforce model explainability metrics.
• Exploratory Reporting:
  Construct high‑impact interactive visualization layers and analytics reports to deliver complex statistical insights to business stakeholders.

• Minimum 5+ years of hands‑on experience in data science, machine learning, statistical modelling, or applied AI solution development.
• Strong ability to translate business and operational challenges into clear data science problems, mathematical formulations, analytical hypotheses and algorithmic solution approaches.
• Hands‑on experience with feature engineering, data preparation, sample selection, model training, hyperparameter optimisation and statistical model validation.
• Strong knowledge of machine‑learning algorithms, including supervised and unsupervised learning, classification, regression, clustering, anomaly detection and predictive modelling techniques.
• Experience building and validating machine‑learning pipelines using Python‑based libraries such as Pandas, Num Py, scikit‑learn, PySpark, Tensor Flow, PyTorch or comparable frameworks.
• Ability to package validated machine‑learning models into production‑ready services using APIs, containers, Docker and microservice‑based deployment patterns.
• Good understanding of model governance, including model monitoring, feature drift, concept drift, latency tracking, explainability metrics and performance degradation analysis.
• Experience creating interactive dashboards, visual analytics and business‑facing reports using tools such as Power BI, Tableau, Plotly, Dash or comparable visualisation platforms.
• Good understanding of secure data handling, data quality, model lifecycle management, documentation and software development lifecycle practices.
• Ability to communicate complex statistical and machine‑learning insights clearly to business stakeholders, technical teams and decision‑makers.
• Ability to work independently as well as part of a distributed project team, collaborating with data engineers, software developers, architects, analysts and business stakeholders.
• Languages:
  
  Flawless bilingual/native‑level business German communications proficiency (C1/C2 level written and spoken) is required. The candidate must present seamlessly in German during the technical panel interview.
• Swiss Compliance:
  Must hold EU/EFTA nationality or possess an active, valid Swiss permanent residency/work card (C Permit or unrestricted B/G Permit).

• Opportunity to work on challenging projects and contribute to the growth of our company.
• Collaborative and dynamic work environment.
• Professional development and growth opportunities.
• Competitive salary and benefits package.