<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <strong>Location: Basel, Switzerland<br/><br/></strong><strong>Contract Duration: 3 years, with possible extension<br/><br/></strong><strong>Experience Required: 3+ years. <br/><br/></strong><strong>Industry Experience: Utilities &amp; Energy</strong> <strong>(</strong><em><strong>Energie &amp; Wasserversorgung) or Telecommunications or Banking &amp; Financial Services or Information Technology &amp; Services<br/><br/></strong></em>Role Overview<br/><br/><strong>We are looking for an experienced Data Scientist to support a long-term enterprise project in Basel. This is a 3-year contract role with the possibility of extension.<br/><br/></strong><strong>We are seeking a senior-tier Data Engineer to design, build, and optimize our enterprise-wide data platform. In this role, you will be responsible for breaking down operational data silos and constructing scalable, low-latency ETL/ELT pipelines. Your mission is to establish a unified data architecture that delivers clean, highly structured, and reliable data streams for downstream business intelligence, advanced analytics, and AI initiatives.<br/><br/></strong><strong>Strategic Scope: Formulates, trains, validates, and deploys scalable statistical analysis models, machine learning systems, and artificial intelligence pipelines to extract actionable predictive trends and enable smart automation systems.<br/><br/></strong><strong>Core Responsibilities<br/><br/></strong><ul><li>Problem Translation: Translate high-level operational and business challenges into precise exploratory data science tasks, mathematical formulations, and algorithmic solution blueprints.</li><li>Model Engineering Loop: Perform structured feature engineering, sample selection, model training, hyperparameter optimization, and statistical validation across diverse algorithm classes.</li><li>Production Microservice Packaging: Wrap validated machine learning pipelines into secure, containerized software microservices exposed via reliable application programming interfaces.</li><li>Governance &amp; Tracking: Establish model monitoring configurations to track feature drift, analyze concept decay, measure latency drops, and enforce model explainability metrics.</li><li>Exploratory Reporting: Construct high-impact interactive visualization layers and analytics reports to deliver complex statistical insights to business stakeholders.<br/><br/></li></ul><strong>Required Skills &amp; Experience<br/><br/></strong><ul><li>Minimum 5+ years of hands-on experience in data science, machine learning, statistical modelling, or applied AI solution development.</li><li>Strong ability to translate business and operational challenges into clear data science problems, mathematical formulations, analytical hypotheses and algorithmic solution approaches.</li><li>Hands-on experience with feature engineering, data preparation, sample selection, model training, hyperparameter optimisation and statistical model validation.</li><li>Strong knowledge of machine learning algorithms, including supervised learning, unsupervised learning, classification, regression, clustering, anomaly detection and predictive modelling techniques.</li><li>Experience building and validating machine learning pipelines using Python-based data science libraries such as Pandas, NumPy, scikit-learn, PySpark, TensorFlow, PyTorch or comparable frameworks.</li><li>Ability to package validated machine learning models into production-ready services using APIs, containers, Docker and microservice-based deployment patterns.</li><li>Good understanding of model governance, including model monitoring, feature drift, concept drift, latency tracking, explainability metrics and performance degradation analysis.</li><li>Experience creating interactive dashboards, visual analytics and business-facing reports using tools such as Power BI, Tableau, Plotly, Dash or comparable visualisation platforms.</li><li>Good understanding of secure data handling, data quality, model lifecycle management, documentation and software development lifecycle practices.</li><li>Ability to communicate complex statistical and machine learning insights clearly to business stakeholders, technical teams and decision-makers.</li><li>Ability to work independently as well as part of a distributed project team, collaborating with data engineers, software developers, architects, analysts and business stakeholders.</li><li>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 (Anbieterfachgespräch).</li><li>Swiss Compliance : Must hold EU/EFTA nationality or possess an active, valid Swiss permanent residency/work card (C Permit or unrestricted B/G Permit). </li><li>What We Offer:**</li><li> Opportunity to work on challenging projects and contribute to the growth of our company</li><li> Collaborative and dynamic work environment</li><li> Professional development and growth opportunities</li><li> Competitive salary and benefits package<br/><br/></li></ul><strong>Recruitment Process – AI Screening with TARA<br/><br/></strong><ul><li>As part of our recruitment process, candidates may be invited to complete an initial AI-powered screening with TARA, the ALLPS.AI interview agent.</li><li>TARA helps us make the hiring process faster, fairer, and more consistent by asking structured, role-relevant questions based on the job requirements. The interview is designed to understand your experience, skills, motivation, and suitability for the role.<br/><br/></li></ul><strong>The AI screening interview may include:<br/><br/></strong><ul><li>Questions about your professional background and relevant experience</li><li>Role-specific technical or functional questions</li><li>Questions about your motivation, availability, and communication skills</li><li>The interview can usually be completed online in 15-20 minutes at a time that is convenient for you. Your responses will be reviewed as part of the overall selection process, together with your CV, application details, and any follow-up interviews with the hiring team.<br/><br/></li></ul><strong>Candidate Experience.:<br/><br/></strong><ul><li>We use AI to support the recruitment process, but final hiring decisions are made by people. Human recruiters and hiring managers remain involved in reviewing candidates and making selection decisions.</li><li>We are committed to a transparent, respectful, and fair candidate experience. Your data will be handled confidentially and in accordance with applicable data protection requirements.<br/><br/></li></ul><strong>If you are a motivated and experienced Data Scientist looking for a new challenge, please submit your application, including your resume and a cover letter, to our website. We look forward to hearing from you.</strong> </div>