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Bold Metrics

AI-powered digital twin sizing & recommendations

Data Scientist - Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeRemote in BrazilNo salary listed

About the Job

Requirements

  • A BSc or MSc in Mathematics, Computer Science, Engineering, or a related field.
  • More than 3 years of hands-on experience in data science, machine learning, and deep learning.
  • More than 4 years of high proficiency in Python and SQL.
  • Practical expertise in A/B testing and causal inference.
  • Extensive experience with AWS cloud technologies.
  • Experience and proficiency in MLOps practices, including model deployment and monitoring.
  • Experience with Docker for containerization and Git for version control.

Responsibilities

  • Lead strategic decision-making for user growth and product innovation using data science tools, including analytics, experimentation, forecasting, and machine learning, to enhance the consumer experience.
  • Develop and deploy machine learning models and causal inference techniques at scale, from concept through measurable business impact.
  • Design and oversee experiments and analyses to evaluate product performance and drive continuous improvements.
  • Build and maintain automated, scalable data pipelines supporting reporting, data visualization, analytics, and machine learning for internal products and solutions.
  • Lead the design and management of comprehensive machine learning platforms, ensuring robust model development and deployment processes.

About the Company

Bold Metrics

AI-powered digital twin sizing & recommendations

Bold Metrics provides AI-powered digital twin technology for the apparel industry, creating shopper-specific digital representations and predicting 50+ body measurements without physical tools. Its SaaS platform analyzes customer data with machine learning to generate accurate measurements and fit predictions, which brands use to offer per-style size recommendations through their e-commerce platforms. The company differentiates itself by delivering individualized sizing insights at the shopper level and supplying data-driven inputs for design and merchandising, rather than generic sizing guidance. Its goal is to help fashion brands reduce online returns, boost sales, and foster customer loyalty through better fit and personalized recommendations.

Company size
11-50
Company stage
Series A
Total funding
$12.9M
Headquarters
San Francisco, CA
Founded
2014

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