Machine Learning Scientist

3 - 7 years

0 Lacs

Posted:3 days ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

The company believes in conducting business every day based on core values of Inclusion, Innovation, Collaboration, and Wellness, ensuring a global team works together with customers at the center. As part of the team, you will have the opportunity to impact the business by identifying AI ML opportunities and building solutions that drive results. You will lead ML projects, conduct research to discover new ML techniques, and innovate to enhance team and business efficiencies. Collaborating closely with engineers, analysts, and leaders, you will implement and optimize ML models, establish best practices for model management, deployment, and monitoring, and integrate ML models into products and services. Additionally, you will assist in troubleshooting technical issues, maintain documentation, project tracking, and quality controls. The ideal candidate will have a degree in engineering, science, statistics, or mathematics, possessing a strong technical background in machine learning. Excellent communication skills, an analytical mindset, and a passion for problem-solving are essential. Candidates should have at least 3 years of hands-on experience in problem-solving using Machine Learning, proficiency in Python or Java, and familiarity with technologies like Spark, Hadoop, BigQuery, and SQL. Deep knowledge of machine learning algorithms, explainable AI methods, GenAI, and NLP is required, along with experience with Cloud frameworks such as GCP and AWS. Experience in Lending and Financial services is considered a plus. The company offers a range of benefits, and it is committed to Diversity and Inclusion. To understand more about the company's culture and community, visit https://about.pypl.com/who-we-are/default.aspx. If you are interested in joining the Talent Community or have any questions related to your skills, please don't hesitate to apply, as the company values all candidates and aims to bridge the confidence gap and imposter syndrome.,

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