Job Description
As a Manager of Data Science at Publicis Sapient in the DACH region, you will assume a technical leadership role in our innovative projects, spearheading initiatives related to customer intelligence, generative AI, language modelling, and personalization. Often leading small project teams by example, you will be responsible for the end-to-end data science lifecycle, from conception to successful production deployment. In this client-facing capacity, you will leverage your technical prowess in machine learning and cloud technologies, providing strategic guidance and driving technical excellence.
Your Impact
- Lead and mentor small project teams, fostering a collaborative and innovative environment
- Take ownership of project outcomes, ensuring they align with client expectations and internal standards
- Lead the development and implementation of advanced machine learning models, ensuring a high standard of technical excellence
- Design, implement and provide guidance on ML engineering workflows, streamlining the deployment of models and systems to production for optimal efficiency
- Collaborate closely with clients, understanding their unique needs and challenges
- Drive the creation of compelling value propositions and client proposals, showcasing the substantial business impact of our data science solutions.
- Innovation and Knowledge Leadership
- Actively contribute to internal data and AI forums, providing thought leadership and fostering knowledge sharing
- Stay at the forefront of industry trends, ensuring our solutions remain innovative
Qualifications
Your Skills and Experience
Quantitative educational background, preferably in a field related to data science, e.g. Computer Science, Statistics, Mathematics, Engineering, or similar fieldsExtensive full-time experience in Data Science roles, with a proven background in leading and mentoring small data science project teamsAbility to be hands-on independently, as part of senior teams, as well as leading small teamsDemonstrated technical proficiency in machine learning, cloud technologies, SQL, and PythonExpertise in collaborative development tools and practices, including peer code reviews and version control (Git)Track record of successfully taking multiple data science models / systems into productionAttention to detail and excellent communication, presentation, and analytical skills; Ability to simplify complex analyses and make concrete recommendationsA demonstrated willingness to learnFluent in German (verbal and written, business environment, complex concepts) and EnglishSet Yourself Apart With
Exceptional ML engineering knowledge, showcasing the Ability to streamline model deployment and manage complex ML workflowsContributions to thought leadership and knowledge sharing within the data science community