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Data Scientist-2

Zoek Pin Chennai, Tamil Nadu

Permanent (Full time)

Posted 43 days ago

Job Description 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 375 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’s Global Data Science team is looking for a Data Scientist to help us develop and enhance machine learning capabilities to innovate and improve our Payment products. You will interact with cross functional teams to: Design, develop and implement data-driven strategies and machine learning models for card auth optimization and conversion improvement Create innovative features and data for payment strategies and models, align with stakeholders and implement these capabilities Analyze and monitor data science solutions, and communicate analysis results and complex concepts in a clear and effective manner Collaborate with other data scientists, product managers and engineers to formulate innovative ideas, and test / implement through advanced data science technique Lead multiple projects focusing on impact as well as mentor junior members of the data science team Job Description:  PayPal’s Global Data Science team is looking for a Data Scientist to help us develop and enhance machine learning capabilities to innovate and improve our Payment products. You will interact with cross functional teams to: Design, develop and implement data-driven strategies and machine learning models for card auth optimization and conversion improvement Create innovative features and data for payment strategies and models, align with stakeholders and implement these capabilities Analyze and monitor data science solutions, and communicate analysis results and complex concepts in a clear and effective manner Collaborate with other data scientists, product managers and engineers to formulate innovative ideas, and test / implement through advanced data science technique Lead multiple projects focusing on impact as well as mentor junior members of the data science team Job Requirements:  Professional industry experience in a quantitative analysis role (4+ years preferred), with advanced degree in Math, Statistics, Operations Research, or Computer Science Proficiency in languages used for querying (. SQL/Hive/Pig), preprocessing (. Unix/Python), and statistical analysis (. Python/R) Experience with machine learning algorithms and statistical methods Strong verbal and written communication skills to express data science concepts and solutions to product managers, data scientists, business partners of varying technical levels, and influence and negotiate to reach alignment on how to execute strategies and improve models. Knowledge about marketing, e-commerce and payments is a strong plus 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 Behaviors 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.

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