Two Plead Guilty in Scheme to Manipulate Amazon Marketplace

The conspiracy used confidential data to give certain sellers an advantage.

Amazon office, San Francisco, Aug. 2019.
Amazon office, San Francisco, Aug. 2019.

SEATTLE (AP) — Two more defendants have pleaded guilty for their role in a multimillion-dollar scheme to manipulate the Amazon Marketplace e-commerce platform.

Six people have been charged in the conspiracy, which federal prosecutors say involved paying bribes to get Amazon employees and contractors to leak confidential data and to use that data to grant certain sellers a competitive advantage on Amazon Marketplace.

Joseph Nilsen, 32, and Kristen Leccese, 33, both of New York, entered their pleas Monday in U.S. District Court in Seattle, acknowledging they paid more than $100,000 in bribes from 2016 to 2020.

Another player, Rohit Kadimisetty, was sentenced in February to 10 months in prison and ordered to pay a $50,000 fine.

Two other defendants — Ephraim Rosenberg, of New York, and Hadis Nuhanovic, of Acworth, Georgia — are set for trial in October. The sixth defendant, Nishad Kunju, of Hyderabad, India, has not been brought to the U.S. to face charges.

In their plea agreements, Nilsen and Leccese admitted they conspired to pay bribes to obtain confidential Amazon business information; to get suspended third-party sellers and product listings reinstated on the Marketplace; to circumvent Amazon restrictions on certain products; and to manipulate customer reviews, among other things.

Nilsen and Leccese are scheduled for sentencing in U.S. District Court in Seattle on Sept. 9. Nilsen pleaded guilty to conspiracy to commit wire fraud, which is punishable by up to 20 years in prison; conspiracy to violate the Travel Act, which bars interstate or foreign travel in aid of racketeering and is punishable by up to five years; and tax charges that can bring up to three years.

Leccese pleaded guilty to conspiracy to violate the Travel Act.

The U.S. Attorney's Office in Seattle agreed to recommend prison terms within guideline ranges for each.

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