Senior Data Scientist – Machine Learning

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Deliver technical solutions for new features while supporting existing functionalities.

• Design and specify machine learning and data solutions tailored to meet business requirements.

• Create predictive models and machine learning algorithms to address intricate business challenges.

• Perform data exploration, preparation, and analysis tasks, spanning from model conception to validation.

• Analyze results and generate insights that emphasize measurable business impact.

• Identify key business questions and develop datasets capable of providing answers.

• Implement, refine, and optimize data platforms and solutions based on streaming and distributed processing.

• Design, develop, and manage solutions utilizing AWS Analytics and Machine Learning services.

• Employ supervised learning, unsupervised learning, and deep learning techniques as dictated by project requirements.

• Utilize experimentation, versioning, and model monitoring tools to ensure quality delivery.

⛳️ Requirements

• Strong programming logic and problem-solving abilities.

• Proven experience in designing and detailing solutions.

• Practical experience with Python.

• Direct experience in machine learning.

• Familiarity with natural language processing (NLP) and/or computer vision.

• Experience with AWS Analytics and Machine Learning services, including Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, and Amazon SageMaker.

• Experience in implementing data platforms.

• Hands-on experience in implementing and optimizing solutions using Kinesis, Kafka, Spark, and/or Storm.

• Experience in designing, developing, and operating solutions with Amazon Kinesis, Apache Kafka, Apache Spark, Amazon SageMaker, Amazon EMR, NoSQL technologies, and third-party solutions.

• Proficiency with tools such as TensorFlow, PyTorch, Scikit-learn, Flink, Spark, Sqoop, Flume, Kafka, and Amazon Kinesis.

• Knowledge of data science libraries and tools such as Scikit-learn, XGBoost, LightGBM, Statsmodels, SciPy, Jupyter, Databricks, and MLflow.

• Ability to thrive in dynamic environments.

• Strong skills in dependency management and cross-team alignment.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health benefits package.

• Opportunities for professional growth and development.

• Flexible working hours and remote work options.

• Collaborative and innovative work environment.