Senior Data Scientist
vor 3 Wochen
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Senior Data Scientist (MLOps)Locations: Berlin, Zurich
Apply for this roleTechnologyTechnologyIn short
As a Data Scientist with MLOps experience your mission is to maximize the power of our database by building efficient artificial intelligence systems and to advance our predictive automation capabilities tackling business challenges across loyalty, retention, customer acquisition, channel attribution and omnichannel presence.
You assess, analyze, and organize large amounts of data to execute experiments and optimize machine learning models pursuing data-driven insights. You build scalable data products working closely together with business teams aiming to shape the strategic roadmap and optimize performance; all towards realizing On's business goals and long-term vision.
Your Mission- Develop data-driven products, train and optimize classifiers and prediction models, productionize and monitor complex ML systems using MLOps techniques and construct data pipelines integrated with our digital products to solve difficult business challenges and to contribute to smart decision-making.
- Analyze and leverage big data and conduct statistical inference focusing on the whole customer journey including all touchpoints and translate these findings into actionable strategies.
- Ensure algorithms generate accurate user recommendations and interpret these findings to drive decision-making and interact with key stakeholders like Digital Marketing, Customer Experience or Product Development Teams outlining strategies and pursuing the realization of our shared company objectives.
- You have 4+ years of experience as a Data Scientist with good MLOps exposure in a Direct-to-Consumer/E-commerce business environment with a clear understanding of prediction models, classifiers, marketing channel mix, attribution, user behavior, website performance, etc.
- You have experience in building end-to-end machine learning pipelines with automated performance monitoring, dynamic model retraining and handling real-time inference in a production environment
- You have knowledge of and experience with software architecture, ML and MLOps frameworks (for example Vertex AI, TF, Kubeflow Pipelines, TensorFlow Extended, Airflow, Docker etc. Flask, Apache Spark, Kafka knowledge is a plus).
- You are proficient in applied statistics, bayesian testing, forecasting, incrementally testing and in experiments such as causal impact analysis. Familiarity with Marketing-mix models is a plus.
- You are familiar with digital marketing and customer experience strategies.
- You feel comfortable working in dynamic and fast moving environments, you have a proactive attitude and you are constantly looking for new challenges.
- You have impeccable analytical and problem-solving skills
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