5 data management jobs found in Berlin

Company: Oliver Wyman Description: Who we are Oliver Wyman is a global management consulting firm. We work with clients through their most defining moments, combining deep industry knowledge, specialized expertise, and the power of perspective to help them adapt, grow, and thrive. We believe diverse perspectives make the work stronger. Our consultants bring different backgrounds, experiences, and ways of thinking to help solve complex problems and create lasting impact for clients, colleagues, and communities. At Oliver Wyman, we are proud of the values ​​that we aspire to live by. We are committed to creating an inclusive environment where everyone can thrive and reach their full potential. Within Oliver Wyman, the Data & Analytics (DNA) division was established in 2017 and operates globally, with a particular focus on Europe. We are a dynamic and rapidly growing team of quantitative analytics specialists, collaborating closely with colleagues across the...

Purpose of the Role Data sits at the heart of the company. This role ensures that Awin can fully leverage the data available across the group, enabling the development of advanced analytical and machine learning capabilities that support stronger commercial decision-making and enhance products used by client-facing teams. As a Senior Data Scientist, you will apply advanced statistical techniques, machine learning methods, and analytical approaches to solve complex business problems and deliver actionable insights that guide business strategy. Working across areas such as forecasting, recommendation systems, network intelligence, experimentation, and predictive modelling, you will lead the design, development, evaluation, and deployment of scalable solutions that create measurable business impact. You will work closely with business stakeholders, Product, Engineering, and Data teams to identify opportunities, shape problem definitions, and translate business challenges...

BERLIN, DÜSSELDORF, HAMBURG, COLOGNE, HYBRID, MUNICH Tasks Developing new ideas   to optimize and revolutionize work processes at our customers' sites. Implementation of customer-specific use cases   throughout the entire AI lifecycle. Identifying patterns and trends   while simultaneously translating technical results into   actionable recommendations   and   presenting   the results to the relevant department and management. Close collaboration   with data engineers and other stakeholders to build ETL pipelines, conduct A/B tests, and integrate models into production systems. Participation   in exciting projects across various industries (large companies and medium-sized businesses in the areas of banking, insurance, automotive, retail, etc.) Expand   your   professional   skills through   interdisciplinary   collaboration and targeted training in the areas of data engineering, cloud architecture and data science (individually...

BERLIN, DÜSSELDORF, HAMBURG, COLOGNE, HYBRID, MUNICH Tasks Developing new ideas to optimize and revolutionize work processes at our customers' sites. Implementation of customer-specific use cases throughout the entire AI lifecycle. Identifying patterns and trends while simultaneously translating technical results into actionable recommendations and presenting the results to the relevant department and management. Close collaboration with data engineers and other stakeholders to build ETL pipelines, conduct A/B tests, and integrate models into production systems. Participation in exciting projects across various industries (large companies and medium-sized businesses in the areas of banking, insurance, automotive, retail, etc.) Expand your professional skills through interdisciplinary collaboration and targeted training in the areas of data engineering, cloud architecture and data science (individually customizable)...

Big tasks Development, implementation and optimization of machine learning models at the proof-of-concept level Scaling of machine learning models for use in production systems, taking into account performance, scalability and security. Design, testing and management of data pipelines for training and production systems Data acquisition, quality assurance, and feature engineering Close and independent collaboration with data scientists, software developers and other teams to integrate models into existing workflows Research, evaluation and selection of suitable machine learning algorithms and technologies, based on current research findings Target-group-oriented documentation and presentation of the developed models and their results Ideal conditions Studies in Computer Science, Computer Engineering, Mathematics, Statistics, Engineering or a comparable field of study Relevant experience in the development and implementation of machine learning...