Paypal : Data Scientist

Brief Description of position:

Fueled by a fundamental belief that having access to financial services creates opportunity, PayPal (NASDAQ: PYPL) is committed to democratizing financial services and empowering people and businesses to join and thrive in the global economy. Our open digital payments platform gives PayPal’s 360+ million active account holders the confidence to connect and transact in new and powerful ways, whether they are online, on a mobile device, in an app, or in person. Through a combination of technological innovation and strategic partnerships, PayPal creates better ways to manage and move money, and offers choice and flexibility when sending payments, paying or getting paid. Available in more than 200 markets around the world, the PayPal platform, including Braintree, Venmo and Xoom enables consumers and merchants to receive money in more than 100 currencies, withdraw funds in 56 currencies and hold balances in their PayPal accounts in 25 currencies.

PayPal prides itself on providing experiences that power Customer Success on our platforms. We believe that conversational experiences and automation can provide valuable experiences for our customers by enabling immediate help in a way that is interactive and adapts to the customer's needs. The next-gen platforms that we build meet customer service needs across a variety of channels including Chatbot, Chat, Voice, Asynchronous Messaging and Self-Service. Our platform aims to resolve customer pain points efficiently, effectively and proactively through the use of AI/ML to accurately predict a customer's likelihood to need help and the intent behind seeking help. Our platforms also equip our customer support agents with tools to resolve customer problems quickly and comprehensively. These tools and experiences include AI/ML driven automation, Natural Language Understanding models, guided solution workflows, and compelling user interfaces.

We are looking for a Data Scientist who will work on ML/DL models to cater to the needs of Customer Success organisation, work with managers and operations to ensure that models meets reliability, accuracy, reusability and performance goals.

  • Bachelors/Masters or higher degree in Computer Science or related technical field.
  • 4 to 8+ years of experience in Statistics, Machine learning and Deep learning.
  • Strong experience in Predictive Analytics is a plus.
  • Strong experience in Natural Language Processing is a plus.
  • Strong experience in developing, deploying and monitoring large scale models in production environments.
  • Demonstrate technical skills by influencing the team on technical decisions and problem-solving approaches.
  • Good knowledge of data structures, algorithms and excellent problem-solving skills (Python/Java/Node)
  • Deep understanding and working knowledge of frameworks like PyTorch/TensorFlow/Keras.
  • Excellent communication, analytical and evaluative thinking skills.

We're a purpose-driven company whose beliefs are the foundation for how we conduct business every day. We hold ourselves to our One Team Behaviours which demand that we hold the highest ethical standards, to empower an open and diverse workplace, and strive to treat everyone who is touched by our business with dignity and respect. Our employees challenge the status quo, ask questions, and find solutions. We want to break down barriers to financial empowerment. Join us as we change the way the world defines financial freedom.

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities.

Location
Bangalore
Minimum Qualification:
Graduate
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