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Product Support Coordinator - Talent Pool - Tommy Hilfiger Global

PVH (Calvin Klein, Tommy)

Product Support Coordinator - Talent Pool - Tommy Hilfiger Global

PVH (Calvin Klein, Tommy)

·

On-site

·

Full-time

·

2w ago

Design Your Future at PVH

  • Product Support Coordinator
  • Talent Pool
  • Tommy Hilfiger Global

Shape the Future of Fashion Operations With Us!

Early Years Fashion Talent & Fashion Graduates — we want to hear from you!

Are you ready to kick-start or grow your career in the world of fashion and product operations? Do you see yourself working behind the scenes with one of the biggest brands in the industry? Then join our global Talent Community, recruiting for our Tommy Hilfiger Product team at our HQ in Amsterdam!

Whether you’re just starting out or already building your expertise in fashion business coordination, we’re looking for driven, detail-oriented individuals with a passion for fashion, product, and teamwork.

Register your interest today to be considered for upcoming roles — your next opportunity might be just one click away. Even if you’ve applied before, we encourage you to re-register and stay connected.

We will review your application against any suitable roles. When we have an open role, we will be in touch.

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About PVH (Calvin Klein, Tommy)

PVH (Calvin Klein, Tommy)

Famous for its designer underwear and denim lines in the 1980s, specializes in mass-market ready-to-wear clothing for all genders and age groups as...

10,001+

Employees

New York

Headquarters

Reviews

4.3

15 reviews

Work Life Balance

3.7

Compensation

4.9

Culture

4.2

Career

4.6

Management

4.0

84%

Recommend to a Friend

Pros

Working on cutting-edge AI/ML technologies

Strong research and publication culture

Top-tier compensation with excellent equity

Cons

High expectations and pressure to deliver

Ambiguity in rapidly evolving field

Extremely fast-paced with constant changes

Interview Experience

44 interviews

Difficulty

3.9

/ 5

Duration

21-35 weeks

Offer Rate

22%

Experience

Positive 67%

Neutral 21%

Negative 12%

Interview Process

1

Recruiter Screen

2

ML Coding

3

ML System Design

4

Research Discussion

5

Team Interviews

Common Questions

ML fundamentals

Design an ML system

Research paper discussion

Statistical concepts