swissQuant Group provides quantitative services, consultancy, and premium product solutions for local and global clients, including several global Fortune 500 companies. Our business edge originates from the effective translation of intelligent technology into measurable client value.
swissQuant's expertise is internationally recognized with its selection as one of the World’s 100 most innovative AI Tech Companies in financial services, and as one of the world’s 100 most innovative WealthTech Companies.
- Responsible for developing and managing data-oriented systems for business (e.g., Trade Recommendation, Structured Products Risk Analyzer, Anti-Money Laundering, Fraud/Outlier Detection, etc.)
- Lead the Big Data Analytics team consisting of data scientists and developers in Zurich
- Responsible for business development, generating leads as well as building and managing client pipeline of the business area Big Data Technologies
- Pitching swissQuant’s solutions to prospective clients
- Own and drive strategy of swissQuant's products related to data analytics and applied machine learning for the financial sector
- Grow key relationships with existing and prospect customers and drive deliverables across all ongoing and future projects
- Dilligently improve and develop existing products ensuring continued relevance, scale and market suitability
- Work closely with other teams within swissQuant, as well as existing and potential customers to help grow our business in new areas
- Contribute to design architecture and play a key part in software implementation, in close collaboration with the team and other swissQuants
- Apply best practices to ensure scalability and efficiency
- Actively participate in selection of best-fit and implementation of cutting-edge data science methodology
- Master or PhD degree in Computer Science, (Financial) Engineering or Data Science
- At least 3 years (5 – 8 years for senior position) of relevant work experience in data science consulting and/or implementation projects in the financial services or utilities space
- Proficiency in Python (e.g. Tensorflow, good grasp of PEP coding standards). Java or C knowledge is a plus
- Strong knowledge of deployment, testing and continuous integration tools (e.g. Docker, Kubernetes, Jenkins, Python unit- and testing suites)
- Knowledge of distributed / parallel computing frameworks (e.g. Spark, Dask, Multiprocessing)
- Experience in architecture development and understanding of common design patterns
- A Self-starter personality eager to learn and further develop skillset
- An excellent communicator with excellent command of English and German.
- Performance and revenue driven