Data Scientist - AI, Data & Analytics Center of Expertise

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Your role

Are you passionate about data, programming and automatization? Do you have technical expertise in design, development, coding, testing and debugging of software? Do you want to design and further develop next generation business applications

As a Data Scientist you will collaborate with our data science and business teams to build state of the art machine learning models, alongside performing exploratory analysis on new and existing data to identify, investigate and solve challenges. You should be comfortable in applying a variety of techniques to find the best result and able to research new methods to trial. You’ll work closely within a small team and collaboration will be key, working together to achieve a common goal.

We’re looking for a Data Scientist to:

• collaborate with the business to assess opportunities for AI/data analytics technologies and maximize their value/impact for our clients. 
• support the design of AI/data analytics solution architecture and work with stakeholders to come up with implementation roadmaps. 
• support AI/data analytics solution implementation and deployment. 
• develop, maintain and deploy machine learning & natural language processing pipeline and models with high performance, quality, and stability. 
• partner with the business by working with their data science teams to integrate AI and machine learning solutions into the group-wide AI, Data and Analytics (ADA) ecosystem – models and data may span across a variety of domains, including, but not limited to: natural language processing (such as document classification, named entity recognition, topic modelling, advanced and semantic information search, extraction, etc.), data analytics (predictive modelling, time-series analytics, pattern recognition, recommendation engine), computer vision (OCR, face recognition) or voice recognition (speech to text)

Your Career Comeback

We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback.

Your team

We are a growing team working at the forefront of Artificial Intelligence and Data & Analytics initiatives at UBS. As the Group Artificial Intelligence, Data & Analytics Centre of Expertise, we closely interact with our business professionals and data scientist teams across the bank. At the end of the day, we want to enable them to build, leverage and scale innovative data and AI solutions to unlock the hidden value and insights in our data. We are constantly expanding our technical expertise into new areas, thus advancing and expanding the UBS AI, Data & Analytics ecosystem. Our team has recently been founded and you will have the unique opportunity to further shape and establish our footprint in the organization. Together, we create a culture defined by curiosity, responsibility and engagement, where our talented people are empowered and inspired to drive extraordinary innovation at speed.

Diversity helps us grow, together. That's why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.

Your expertise

• experience in designing and developing enterprise-scale NLP solutions in the areas of: Named Entity Recognition, Document Classification, Document Summarization, Topic Modelling, Sentiment Analysis and OCR text processing 
• experience building ML & NLP solutions using common ML libraries and frameworks, i.e., Pandas, Sklearn, TensorFlow, SparkML, Pytorch, Keras, spaCy 
• strong knowledge and working experience with NLP/ML & algorithms and models (GLMs, SVM, PCA, NB, Clustering, DTs) and their underlying computational and probabilistic statistics excellent statistical skills in applied regression, spatial and time series modeling.
• 3-5 years of practical programming experience in Python and optionally R experience in setting up supervised and unsupervised learning ML/NLP models including data cleaning, developing data pipelines (both structured and unstructured), data analytics, feature creation, model selection and ensemble methods, performance metrics and visualization

It would be a plus if you have:

• profound knowledge of MLops concepts
• exceptional academic track record with an advanced degree 
• knowledge of Explainable AI concepts

  • knowledge of other programming languages such as Scala, C/C++, Matlab, PHP, Django, SQL/Postgres, Pytorch ASM, OpenCL, etc.