Manager, Product Data Science at PayPal

San Jose, California, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

21 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Data Analysis, SQL, Python, R, Statistics, Causal Inference, Experimentation, Mentoring, Cross-Functional Collaboration, Data Quality, Reporting Systems, Data Modeling, Communication, Problem-Solving, Product Analytics

Industry

Software Development

Description

Lead and manage data science projects, ensuring timely delivery and alignment with business goals. Develop and maintain data models, algorithms, and reporting systems to support data analysis and decision-making. Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives. Collaborate with cross-functional teams to understand data needs and provide actionable insights. Ensure data quality and integrity through regular audits and validation processes. Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement. Perform deep-dive analytics including Causal Inference analysis, Pre-Post analysis, Sensitivity analysis, financial projections, and additional ad-hoc exercises to provide holistic recommendations for segment level Pricing optimizations Challenge the status quo, and drive data backed decision making Partner closely with product leaders to understand new product offerings being built and recommend the right metrics to measure the performance of those features Identify key metrics, conduct rigorous explorative data analysis, create executive-friendly info-insight packets and build business cases that drive decision making and prioritization Analyze business performance and health, triage issues, and provide recommendation on the best course solution and optimization Synthesizing large volumes of data with attention to granular details and present findings and recommendations to senior-level stakeholders Collaborate with engineering and data engineering to enable feature tracking, resolve complex data and tracking issues, and build necessary data pipelines Define and cultivate best practices in analytics instrumentation and experimentation Support multiple projects at the same time in a fast-paced, results-oriented environment Mentor junior analysts on complex analyses 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. At least 10 years of experience analyzing large, multi-dimensional data sets and synthesizing insights into actionable solutions At least 2 years of experience in managing data science and analytics teams B.S. in a quantitative field, advanced degrees preferred Fluent in SQL and scripting languages such as Python or R, comfortable working with large, complex, and potentially messy datasets Understanding of statistics (e.g. hypothesis testing, statistical inference, regression) and experience designing and evaluating complex experiments Exceptional communication skills, both written and verbal, to influence cross-functional teams Strong interpersonal skills and experience leading cross-functional teams Prior work experience in a product analytics space would be highly valued A passion for problem-solving and comfort with ambiguity

Responsibilities

Lead and manage data science projects, ensuring timely delivery and alignment with business goals. Collaborate with cross-functional teams to understand data needs and provide actionable insights.