- Location
- Brazil
- Level
- Mid level
- Posted
- 24 months ago
About this role
Please submit your resume in English. Applications in other languages may not be considered.
Bold Metrics is the leading fit and sizing solution on the market today for the world’s top retailers and brands. We are a venture-backed startup that is making a big impact on the environment, forever changing the landscape of eCommerce. We are a remote-first company that is full of inspiring and friendly people.
We are currently searching for a Data Scientist to join our fast-growing team. This position is for someone located in Brazil and working remotely, however if you're located in São Paulo, you will be able to come into the office location as needed. In this position you will have the opportunity to work with some of our biggest projects within the retail industry.
About You:
You are a humble, passionate, and experienced engineer that is looking for a collaborative and analytical Data Scientist role to support the execution of our product deliveries and machine learning pipeline. This comprises validating the data flow from data sources, analyzing patterns and trends in the data, and facilitating machine learning updates to the system.
As our Data Scientist, you are an extremely detail oriented, out-of-the-box problem solver with a commitment to doing high-quality work. You will work closely with the Engineering and Data Teams, alongside Customer Success teams to support the flow of data collection and machine learning initiatives to ultimately drive customer success.
How You Will Make an Impact:
- Lead strategic decision-making for user growth and product innovation by utilizing the full range of data science tools, including analytics, experimentation, forecasting, and machine learning, to enhance the entire consumer experience.
- Develop and deploy machine learning models and causal inference techniques at scale, from concept to measurable business impact.
- Design and oversee experiments and analyses to evaluate product performance and drive continuous improvements.
- Build and maintain automated, scalable data pipelines to support 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.
Skills and Qualifications: (even if you do not meet these skills 100%, we still welcome you to apply)
- BSc or MSc in Mathematics, Computer Science, Engineering or related field.
- Over 3 years of hands-on experience in Data Science, Machine Learning, and Deep Learning.
- +4 years of demonstrated high proficiency in Python and SQL.
- Practical expertise in A/B testing and causal inference.
- Extensive experience with AWS cloud technologies.
- Must have experience and be proficient in MLOps practices, including model deployment and monitoring.
- Experience with Docker for containerization and Git for version control.
About Us:
Bold Metrics, established in 2017, is a SaaS solution for retailers and brands to reduce returns, improve sustainability and supercharge their supply chain from the ground up. Using a comprehensive set of machine learning and AI technologies to accurately capture customer body measurements, we help apparel brands unlock the power of body data to meet the demands of today's increasingly personalized world.
Learn more about us at boldmetrics.com
We strive to create a place to work where we all feel safe, empowered, engaged and inspired. We are an equal opportunity employer committed to offering employment that is based upon personal capabilities and qualifications without discrimination based on race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability.
© 2025 Bold Metrics, Inc.
As published by Bold Metrics. Applications are handled on their site.
Skills this posting mentions
About Bold Metrics
Bold Metrics Inc. (BMI) has created a suite of AI technologies that allows brands to accurately predict customer body measurements and relate them to garment specifications. Using our cutting-edge machine learning algorithms, retailers and brands are ditching conventional sizing solutions and leveraging our technology to reduce returns and increase conversions. Ultimately, our goal is to revolutionize the apparel industry by giving brands the power to use this data to unlock body-relative apparel design. Historically, apparel sizes have been generated in the absence of customer-driven body data. This has led to a worldwide apparel waste problem caused by a high rate of returns coupled with a bad consumer experience around fit and sizing, often amplified online. Along with garment sizing optimizations, the downstream experience becomes more customer-driven, leading to a significant reduction in returns and happier customers. We are a venture-backed well-funded company and work with some of the world’s largest brands, retailers, and clothing manufacturers in the U.S., Europe, and Asia. Our office is located in San Francisco, CA.
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Queue Machine Learning Engineer (Data Scientist) and I read the posting, rewrite your resume against it, draft the cover letter, and score the fit. Then you press send, or press one button and I fill in Bold Metrics’s form for you.
01Drop your resume
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02I rank the openings
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03Each one is written up
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Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
- New matches ranked and written before you are up.
- Every bullet stays inside what your history supports. Nothing invented.
- Queued, submitted, interviewing, offer: one screen, not a spreadsheet.
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