Senior Data Scientist

🔥 18 hours ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 25%

What it means: how likely this posting is sitting open without active hiring.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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Five Acts

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2005

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Five Acts is a company specialized in building and evolving data platforms using modern technologies and cloud architecture. Through their accelerators and processes, they create data products that deliver value swiftly for businesses. Five Acts focuses on data engineering, analytical intelligence, and machine learning to help companies harness the power of their data, transforming it into actionable insights. With over 300 clients and a strong track record of completed projects, Five Acts is dedicated to helping organizations improve through effective data strategies.

📋 Description

• Develop predictive churn models to identify customers likely to withdraw investments and transfer funds to other financial institutions • Perform exploratory data analysis, feature engineering, model training, validation, and optimization of Machine Learning models • Develop customer segmentation models, identifying behavioral patterns and potential reasons for attrition • Build recommendation engines to support customer win-back and retention strategies • Develop investment portfolio optimization solutions, considering risk profile, liquidity, concentration, investment horizon, and suitability rules • Apply model explainability techniques, such as SHAP, ensuring transparency and traceability of predictions • Implement temporal validation, backtesting, and model performance evaluation processes • Work with financial data from internal systems, Open Finance, and investment information • Develop and operationalize models in Azure Databricks using MLflow, Unity Catalog, and Feature Engineering capabilities • Collaborate on the implementation of batch inference pipelines, model monitoring, and MLOps processes • Support the integration of analytical models with generative AI solutions to produce business insights • Prepare technical documentation and support model validation and governance processes with the client

🎯 Requirements

• Strong experience as a Data Scientist, with hands-on experience developing and deploying Machine Learning models • Proficiency in Python and SQL for data manipulation, analysis, and modeling • Experience with Data Science libraries such as Pandas, NumPy, Scikit-learn, and XGBoost or similar tools • Experience with supervised classification models, churn prediction, and customer segmentation • Knowledge of feature engineering, feature selection, temporal validation, and hyperparameter optimization techniques • Experience with predictive model evaluation metrics, probability calibration, and explainability techniques • Hands-on experience with Databricks for developing and executing analytical models • Knowledge of MLflow for experiment tracking, version control, and model lifecycle management • Knowledge of mathematical optimization techniques applied to problems with multiple constraints • Experience developing reproducible models, preparing technical documentation, and following sound governance practices • Ability to interact with business teams to understand problems, define analytical approaches, and translate results into recommendations • Analytical, investigative, and problem-solving mindset, with the ability to address complex challenges

🏖️ Benefits

• Remote work • Mental Health Program – online and in-person psychotherapy • Support for professional certifications and courses • Partnerships for postgraduate and MBA programs (Esalq/USP) • Partnerships with language schools • Partnerships with gyms and wellness apps (Wellhub) • Internal talks and discussion groups • Employee referral bonus • Happy hours • Gifts and treats on special occasions