Machine Learning and BioBert
- Full-time
Company Description
WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.
We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees. Our global footprint spans 16 countries with 61 delivery centers worldwide including in China, Costa Rica, India, the Philippines, Poland, Romania, South Africa, Spain, Sri Lanka, Turkey, United Kingdom and the United States.
Job Description
Handling failure of artificial intelligence / machine learning / automation tools (i.e. bots, neuro-linguistic programming programs etc.)
▪ Re-configuring existing workflows in Informa’s systems and sub-systems
▪ Editing code to resolve any scraping failures
▪ Configuring modules to fetch correct data
▪ Configuring data sources and setting the frequency for scrapping
Qualifications
Machine learning, NLP, Pyspark, AWS S3, AWS Postgres
Additional Information
Flexible to work in shifts to maintain overlap with UK/US working hours.
Flexible in working outside of core business hours if needed (mostly during releases)
Good communication, analytical and presentation skills, problem solving skills and learning attitude
Experience of developing web applications, including the ability to use and understand advanced features of web browsers
Machine learning, NLP, Pyspark, AWS S3, AWS Postgres
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