Senior Data Scientist – Machine Learning

Job not on LinkedIn

🔥 37 minutes ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Onzze

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2021

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Onzze is an HR-tech company and recruitment partner that connects companies with qualified and diverse professionals using a proprietary talent-attraction platform and dedicated recruiting teams. They specialize in filling challenging technical and product-related roles quickly and accurately—delivering shortlists in days, weekly candidate flows, post-hire follow-up and replacement guarantees—serving startups to large enterprises across technology, product, marketing and data functions.

📋 Description

• Develop and adapt models created by the team, including causal inference–based models, for different business contexts • Plan, execute, and interpret A/B tests • Adjust or retrain models based on experiment results and new data • Validate models from the prototype stage through production deployment using Databricks and Azure • Continuously monitor the performance of deployed models • Detect changes in data (data drift) • Define retraining triggers • Configure alerts when performance degradation occurs • Collaborate with the Senior Data Engineer, Analytics Engineer, and Data Scientist specializing in causal inference • Transform the team’s work into business-adapted models deployed and monitored in production

🎯 Requirements

• At least 6 years of hands-on professional experience in data science and Machine Learning, working in production environments • Proven experience building, deploying, and monitoring statistical and Machine Learning models in production • Strong command of A/B testing methodologies and experimental design • Practical knowledge of causal models and causal Machine Learning, sufficient to understand, adapt, and develop causal inference–based models • Experience with Databricks, PySpark, Python, and Azure • Strong quantitative foundation in Mathematics, Statistics, Computer Science, or related fields • Fluent English • Ability to adapt models to different business contexts and explain the impact of technical decisions and choices to non-technical stakeholders

🏖️ Benefits

• Contractor engagement (PJ) • A master’s or doctoral degree is a plus but is not required for this more applied role

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