AI Data Scientist
Information Technology (IT)
Job Reference #
Do you want to design and build next generation business applications using the latest AI technologies? Are you confident at iteratively refining user requirements and removing any ambiguity? Do you like to be challenged and encouraged to learn and grow professionally? Do you have a proven track record of Data Modelling, Predictive Analytics and Time Series Analysis?
We’re looking for software engineers to:
• provide technology solutions that will solve business problems and strengthen our position as digital leaders in financial services
• analyze business requirements for the IB Client Lifecycle Management suite of applications
• design, plan and deliver sustainable solutions using modern programming languages
• providing technical expertise and recommendations in assessing new software projects and initiatives to support and enhance our existing applications
• conduct code reviews and test software as needed, along with participating in application architecture and design and other phases of SDLC
• see that proper operational controls and procedures are implemented to process move from test to production
You’ll be working in the IB Client Lifecycle Management group, as part of the Investment Banking Technology Operation team. We provide Client onboarding services along with maintenance of static reference data (data including Client, Account, SSI, Instrument, Issuer, Pricing, Book, Product and Calendar). This acts as a critical enabler to the various businesses and logistics functions across the Bank. As a Data Scientist, you’ll play an important role in helping our Investment Bank business to uncover hidden revenue opportunities by enabling effective prioritization of onboarding requests, predicting revenues and TATs. Improving end-to-end efficiency of the processes by identifying blockers by mining and interpreting the data.
• Graduate degree (MS or PhD) in Computer Sciences, Mathematics or a related discipline
• 2+ years of of post-qualification experience in software development
• Hands-on experience and proven success in building Deep Learning-based solutions (Dense & Convolutional NNs, RNNs/LSTMs, Transformer-based models, etc.)
• Advanced understanding of Statistics & traditional ML & optimization methods
• Strong background in both supervised and unsupervised learning techniques
• Solid Python coding experience in the context of Machine Learning (primarily Python >3.6, familiarity with popular ML/Data Science libraries, e.g. numPy, Pandas, scikit-learn
• Proficiency in training large scale models in, at least, one of the following frameworks: TensorFlow, Keras, PyTorch
• Excellent knowlegde of natural language processing (NLP) techniques in the following areas: Machine Translation, Question Answering, Information/Relation Extraction, NER, Sentiment Analysis, Feature modeling, etc.
• Knowledge of the latest SOTA research papers (NLP domain covering the following is a plus: Transformer, BERT, Google Reformer, etc.)
• Good understanding of algorithms and complexities that could translate into an efficient code
• Demonstrated ability to execute across the entire data pipeline
• Excellent knowledge of professional software engineering practices and best practices for the full software development life cycle
• Fluency in using Git and GitHub, Confluence, JIRA, understanding of agile methodologies
• Working knowledge of Big Data technologies (hadoop, spark, flink, kafka, etc.) and /or devops tools(Docker, Kubernetes) is a plus
• Prior experience in financial services and good command of investments-related topics is a plus
• Ability to plan, design and deliver solutions in a large scale enterprise environment
• Ability to prioritize against competing demands and deadlines
• Ability to work collaboratively with on-site and remote teams
• Good written and spoken English communication skills
– go getter, who sets aggressive targets and plans to achieve them
– good leader willing to accept various delivery challenges
– great communicator, you know how to speak with people at all levels
– team player, working with a globally distributed team
Expert advice. Wealth management. Investment banking. Asset management. Retail banking in Switzerland. And all the support functions. That's what we do. And we do it for private and institutional clients as well as corporations around the world.
We are about 60,000 employees in all major financial centers, in more than 50 countries. Do you want to be one of us?
We're a truly global, collaborative and friendly group of people. Having a diverse, inclusive and respectful workplace is important to us. And we support your career development, internal mobility and work-life balance. If this sounds interesting, apply now.
Disclaimer / Policy Statements
UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.