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Data Scientist

Roles & Responsibilities

  • 3+ years of hands-on experience in Machine Learning — forecasting, supervised learning on user data, or both
  • Strong Python skills, including pandas, scikit-learn, XGBoost, statsmodels, and/or Prophet
  • Advanced SQL skills and experience working with cloud platforms (GCP is a plus)

Requirements:

  • Design and execute experiments to improve forecasting metrics across specific segments
  • Perform feature engineering on large-scale transactional data (~5M records in BigQuery)
  • Build user behavior models, including segmentation, propensity, churn, and retention
  • Evaluate models using strict temporal holdout methodologies and segment-level metrics

Job description

At Heinsohn, we partner with clients across North America and LATAM, building innovative solutions in an agile, diverse, and multicultural environment. We are passionate about technology, continuous learning, and collaboration - and we want you to be part of this growth.

We are looking for a Data Scientist to join our team and bring expertise that will contribute to the success of high-impact international projects.

The system already has a defined architecture, production models running in BigQuery ML, and an ARIMA + XGBoost ensemble with validated results in production. Your role will start by optimizing and improving the existing setup, with a clear path toward the next layer of development: user behavior modeling, segmentation, propensity, and retention models.


✨ Responsibilities

  • Design and execute experiments to improve forecasting metrics across specific segments

  • Perform feature engineering on large-scale transactional data (~5M records in BigQuery)

  • Build user behavior models, including segmentation, propensity, churn, and retention

  • Evaluate models using strict temporal holdout methodologies and segment-level metrics

  • Document experiments with clear reasoning — hypotheses, results, and decisions

  • Collaborate with the ML Engineer responsible for maintaining the architecture and production pipelines

✅ Requirements

  • 3+ years of hands-on experience in Machine Learning — forecasting, supervised learning on user data, or both

  • Strong Python skills, including pandas, scikit-learn, XGBoost, statsmodels, and/or Prophet

  • Advanced SQL skills and experience working with cloud platforms (GCP is a plus)

  • Strong model evaluation judgment — you understand why random train/test splits are inappropriate for time series data

  • Experience performing feature engineering from transactional datasets

  • Ability to work within an existing framework and architecture without unnecessarily reinventing established solutions

🌟 Benefits

  • 100% remote work from any LATAM country

  • Opportunity to work on international projects with multicultural teams

  • Culture that encourages professional development and continuous learning

  • Spaces for innovation, well-being, and career growth


Ready to take your talent to the next level?
At Heinsohn, we value innovation, passion for technology, and teamwork. If this sounds like your next challenge, apply today and let’s make history together! ✨

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