clients Spate

Data Operations Manager - Japanese speaker

Location

🇺🇸 USA Only

Job Type

Contract

Experience

N/A

Salary

N/A

Skill Set

Role

Management and Finance

Job Details

About the project

Spate is the machine intelligence platform used by top industry beauty brands. We analyze over 20 billion search signals to spot the next big beauty trend and help brands with their marketing/product development strategies.

As we expand to new Asian markets (Japan), we are looking to hire a Data Operations Manager to help build and manage our expanding datasets. In this role, you will be in charge of overseeing the Spate data expansion and entry process. This role will require a strong eye for detail, and a strong passion for organization and project management. We would be looking at 10 to 20 hours a week (we can be flexible depending on your availability).

Responsibilities

  • Oversee data process and quality assurance for each vertical/market
  • Manage relationships with the data entry team
  • Analyze datasets and investigate discrepancies or inconsistencies
  • Curate interesting and unique trends for Spate content; brainstorm compelling topic ideas for upcoming reports

Requirements

Minimum qualifications

  • 1-3 years of experience
  • Exceptional verbal and written skills
  • Meticulous and organized, with a high level of attention to detail
  • Proven problem-solving skills using deductive reasoning, understanding hierarchical relationships, and identifying gaps in logic
  • Demonstrated project management skills and ability to manage multiple priorities
  • Self-starter and ability to work independently

Preferred qualifications

  • Experience in SEA/SEM and SEO
  • Or Experience in CRM
  • Or Experience in Copywriting

Benefits

About Spate

At Spate, we use data science to predict the next big consumer trend in beauty, personal care & food.

Spate was founded in 2018 by Yarden Horwitz & Olivier Zimmer, two ex-Googlers who led the trendspotting division at Google and uncovered trends such as turmeric, cold brew, and face masks. Spate has been funded by the prestigious Y Combinator incubator and Initialized Capital. We currently have ~90 clients in the U.S., mainly in the beauty space from direct-to-consumer brands to big names such as L’Oréal, Estée Lauder, Unilever...

As two ex-Googlers with a passion for using data to spot new patterns in consumer behavior, and we have made it our mission to build the world’s greatest consumer trends prediction platform of all time. And not just because we want to be trendy, but because we want to help brands get better at giving consumers what they really want.

Brands waste over $200BN every year due to product launch failures and inventory waste. By spotting Turmeric, we were able to tell brands to stop wasting money on kale products and provide consumers with glorious golden milk lattes instead - because that’s what consumers want.

How do we do this? We tap into publicly available consumer data (anonymous and aggregated) to identify interesting shifts in consumer behavior. We leverage the latest available technology in ML to solve problems in ways that have never been explored before.

Why Spate?

  • Join a well-funded company that is working with the top brands in consumer goods
  • Work directly with the founders to set the direction of the company
  • Grow in a fast-paced environment
  • Always be up-to-date on the latest trends!

We enjoy a casual atmosphere, but our culture is about getting things done. We are passionate yet pragmatic when it comes to solving problems in a fast-paced environment. Our standards are high, but we thrive on working with people we respect and can learn from. We’re flexible on work styles, as long as everyone is getting their work done - and getting it done well.

We are an equal opportunity employer where our diversity and inclusion are central pillars of our company strategy. We look for applicants who understand, embrace, and thrive in a multicultural and increasingly globalized world. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.