Data Scientist

hace 1 semana

Córdoba, Córdoba, Argentina Eureka Labs A tiempo completo

Location: Full remote.

Schedule: Full-time, European time zone availability.

Job Purpose

We are seeking a Data Scientist to help build data-powered services that make our product partner smarter and more intuitive. You will utilize advanced analytics techniques, statistical modeling, and machine learning to unlock insights from vast datasets, collaborating closely with cross-functional teams to design and deploy innovative solutions.

Key Responsibilities

  • Drive data-driven product design by generating insights and recommendations from multiple data sources.
  • Develop, train, and deploy Machine Learning models to enhance user experiences and optimize key business metrics.
  • Leverage diverse data sets (with support from our Data Engineering team) to uncover patterns and deliver actionable intelligence.
  • Formulate hypotheses and design experiments to validate model performance in production environments.
  • Democratize data across the organization by creating clear, automated reports and dashboards.

Experience & Qualifications
  • 3+ years of experience as a Data Scientist, working with large datasets in a production environment.
  • Strong foundation in applied statistical techniques for model building and hypothesis testing.
  • Mastery of data manipulation and ML frameworks with Python (pandas, NumPy, scikit-learn, etc.), plus familiarity with prototyping tools like Streamlit.
  • Hands-on experience designing, training, and deploying ML models at scale.
  • Advanced data extraction skills using SQL, Spark, and related technologies.
  • Familiarity with software development tools (Cloud infrastructure, Git, Docker, etc.) and best practices.
  • Proficient in building and optimizing large-scale data pipelines and ETL processes with Spark.
  • Familiarity with CI/CD for ML, experiment tracking, and model serving (e.g., MLflow, Kubeflow).
  • Git: Comfort with basic branching, merging, and pull request workflows.
  • Docker: Capable of containerizing ML solutions for development and deployment.
  • Able to lead projects from conception to production with minimal oversight.
  • Collaborative mindset to work effectively with product managers, engineers, and other stakeholders.
  • Advanced English Level.
  • Terraform: Basic exposure to Infrastructure as Code principles for automating resource provisioning. Nice to have.
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