Data Scientist
UBS
- Pune, Maharashtra
- Permanent
- Part-time
- turn data into an asset across the organization using visualization and other techniques
- collaborate across business units, providing thought leadership and driving day-to-day implementation of the analytics strategy
- advise on potential analytical approaches to business needs, including associated costs and trade-offs, and recommendations
- design, coordinate, and implement analytical business and technology solutions to support innovation initiatives
- effectively use data science toolkits and related visualization technologies to deliver quality analytics and data insight to our stakeholders
- stay on top of current business and industry trends and best practices around data science tools and techniques
UBS RecruitingYour teamYou'll be working in a pod consisting of data scientists and data engineers aiming to deliver AI based solutions to the end users of a Credit Risk monitoring platform. You'll be engaging with analytics projects and functional stakeholders, end users, and colleagues in a number of locations.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.
- 10+ years of programming experience in one or more of the following: Python, Scala, C/C++, Matlab, PHP, Django, SQL/Postgres, Pytorch ASM, OpenCL, etc.
- 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