Manager, Machine Learning 2 Full-time

At PayPal (NASDAQ: PYPL), we believe that every person has the right to participate fully in the global economy. Our mission is to revolutionize commerce globally to make moving money, selling and shopping, personalized and secure.

Job Description Summary:
What you need to know about the role:
As a Machine Learning Manager you will be leading the India Seller Risk ML team.

Meet our team:
Global Seller Risk ML team enables managing seller fulfillment risk for PayPal with the help of highly scalable ML models that enable accurate risk assessment throughout a seller’s lifecycle.

Job Description:

Your way to impact:

You will set up, lead and grow this team from scratch. You will actively partner with Risk Strategy teams to enable frictionless experience for our good sellers, while minimizing the losses from bad actors in the system.

Your day-to-day:

• Work with business partners and stakeholders to understand the business, formulate the problems, come up with the solutions and communicate them back effectively to non-technical audience.
• Lead complex, multifunctional data science projects
• Design, develop and implement real-time, highly complex advance machine learning models to solve business problems.
• Work with large volumes of data; extract and manipulate large datasets using standard tools such as Python, R, H2O, Hadoop and SQL
• Collaborate with engineers to implement models on one of the best data platforms in the industry.
• Analyze data to identify trends, perform root cause analysis and test hypotheses.
• Communicate complex concepts and the results of the models and analyses to technical and non-technical audience.
• Mentor and grow the team.

What you need to bring:

• Bachelors/Masters/Ph D in Computer Science/Data Science with 8+ years of practical experience in building ML models at scale.
• Strong problem-solving and communication skills
• Proven track record of building and implementing machine learning solutions
• Experience in leading cross-functional, highly complex Data Science projects
• Familiar with various Machine Learning algorithms and Statistical methods.
• Strong coding knowledge in Python or other common languages used in ML.

Additional Job Description:

Subsidiary:
PayPal

Travel Percent:
0

Our Benefits:
At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset-you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.
We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com

Who We Are:
Click Here to learn more about our culture and community.

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. For more information, visit https://www.paypal.com , https://about.pypl.com and https://investor.pypl.com.

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. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Any general requests for consideration of your skills, please Join Our Talent Community.