Data Science – Analyst 4
At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
About the team and the role:
eBay, Inc. seeks Data Science – Analyst 4 in San Jose, CA
What you will accomplish:
Job Duties: Create data-driven, strategic business insights by mining the largest datasets in the world of e-commerce and using analytics and data science techniques that drive transformative changes to the customer experience. Drive initiative success by developing product health metrics, running A/B tests to enhance features, building monitoring tools for product health, and creating custom analytics for insights to improve features. Design and implement advanced statistical models and machine learning algorithms. Partner closely with the product, business, and engineering teams, and find opportunities that are accretive to the product roadmaps. Improve and build technical skills to turn big data into Teradata and Hadoop into actionable insights and evaluate how insights impact eBay's ecosystem. Partial telecommuting is permitted from within a commutable distance.
What you will bring:
Minimum Requirements: Master’s degree, or foreign equivalent, in Data Science, Information Science, Statistics, or a closely related field plus two years of experience in the job offered or a related occupation with proven track of record in delivering actionable insights. Employer will accept a Bachelor’s degree, or foreign equivalent, in Data Science, Information Science, Statistics, or a closely related field plus five years of progressively responsible experience in the job offered or a related occupation.
Special Skill Requirements:
1. Experience extracting, cleaning, and manipulating large scale dataset using SQL (2 years)
2. Experience building and developing advanced data science solutions using Python (2 years)
3. Experience visualizing insights and analytical results in intuitive manner using Tableau (2 years)
4. Experience with product feature optimization using A/B Testing at scale (2 years)
5. Experience with basic customer segmentation methodology for a large organization using statistical modeling (2 years)
6. Experience with basic text mining skills for large scale unstructured data set using statistical modeling (2 years)
7. Experience with basic story telling and analytical report to influence stakeholders using Microsoft PowerPoint (2 years)
8. Experience designing and deploying recommendation engines for an ecommerce platform or equivalent using machine learning algorithms (2 year)
Salary: $174,304.00-221,100.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.
Must be legally authorized to work in the U.S. without sponsorship.
Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
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