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Open nowPosted 214 days ago

PRINCIPAL DATA SCIENCE SPECIALIST

charleskeith69 open roles

Where
Singapore
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Your applicationOpen nowPRINCIPAL DATA SCIENCE SPECIALISTcharleskeith · Singapore

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on charleskeith's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. charleskeith postings stay open a median of 8 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 214 days ago

charleskeith median: 8 days open

The posting

We're on the lookout for individuals who are passionate about fashion, think outside the box, and have an eye for innovation.

Unleash your potential with us, and join us as we create joy and excitement in our global community to empower people to express themselves freely through fashion.

• Work closely with business users of the group to build a strong pipeline of impactful projects. This will involve understanding business challenges, evaluating the use cases, scoping the problems, and developing business cases on how to turn data into critical information and knowledge which can then translate into business decisions and actions • Scope, design, develop, deploy, and maintain data science-enabled applications and data analytics applications across the organization • Support the professional growth and development of data scientists and data analysts in your team • Educate and share data analytics and data science knowledge with various departments • Organise and guide your team to execute the pipeline of data science and data analytics projects.

This involves, - Perform data cleaning, pre-processing, and feature engineering to build machine learning models

- Iterate with key users to perform subsequent deep dives based on initial results and fine-tune the models

- Build automation applications or APIs to call the models

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