Python Job: Data Scientist

Job added on

Company

UBS

Location

Zürich - Switzerland

Job type

Full-Time

Python Job Details

Switzerland - Zürich
Information Technology (IT)
Group Functions

Job Reference #

255600BR

City

Zürich

Job Type

Full Time

Your role

Do you want to design and build next generation business applications using the AI technologies as a backbone? Do you enjoy exploring capabilities of emerging technologies and do you like to use them to tackle a real business challenges?

We are looking for a Data Scientist to:

  • Partner and collaborate with the Business, Data Scientist, Machine Learning Engineers and IT teams across the organization to uncover business value using AI-powered solutions
  • Ability to communicate complex models, analysis and recommendations in a clear and precise manner
  • Ability to take an open stack approach towards problem solving and build production ready solutions
  • Perform deep-dive analysis into new topics and manage priorities between research and development effectively
  • Perform analysis to provide input for data and model pipeline, testing and training requirements

Your team

You will be working in the Automation Office, AI & Data Science team based in Zurich. We are a dynamic and diverse team of transformation professionals with a focus to incubate, mature and scale cognitive platforms and extend automation spectrum across the firm, working in close collaboration with partners across the firm.

Your expertise

Required Qualifications:
  • Masters or Bachelors level degree Computer Science or any related quantitative discipline
  • 2+ years professional experience in extracting commercial value to deliver ML/AI solutions
  • Demonstrable industry experience in Data Science/ Machine Learning with experience deploying solution to production
  • Solid understanding of fundamentals of Statistical Natural Language Processing
  • Experience in industry or research using NLP techniques (TF-IDF, LDA, LSTM, NER, Topic Modelling, Embeddings, Transformers etc)
  • Ability to connect theory and practice of Data mining, Information Retrieval and Machine Learning to solve real-world use case
  • Ability to take deep-dive into new and emerging NLP and research topics
  • Strong working knowledge in Python scientific stack, SQL , Unix(awk, sed, bash) for data wrangling, data analysis, modelling

Desirable:
  • Familiarity with (or, at least, a desire to learn) Knowledge Graph, Network Analysis, NLU, sentiment, Speech-to-text
  • Knowledge of visualization tools like Tableau and developer tools like matplotlib and ggplot
  • Exposure to Azure/AWS cloud services
  • Fluency in English is mandatory, German or Swiss-German language would be an advantage

About us

UBS is the world’s largest and only truly global wealth manager. We operate through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management and the Investment Bank. Our global reach and the breadth of our expertise set us apart from our competitors.

With more than 70,000 employees, we have a presence in all major financial centers in more than 50 countries. Do you want to be one of us?

How we hire

This role requires an assessment on application. Learn more about how we hire: www.ubs.com/global/en/careers/experienced-professionals.html

Join us

At UBS, we embrace flexible ways of working when the role permits. We offer different working arrangements like part-time, job-sharing and hybrid (office and home) working. Our purpose-led culture and global infrastructure help us connect, collaborate, and work together in agile ways to meet all our business needs.

From gaining new experiences in different roles to acquiring fresh knowledge and skills, we know that great work is never done alone. We know that it's our people, with their unique backgrounds, skills, experience levels and interests, who drive our ongoing success. Together we’re more than ourselves. Ready to be part of #teamUBS and make an impact?

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.