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Data Scientist

mayflower (recruitee) · Limassol, Lemesos, Cyprus

Data Science / AI / Machine LearningQuick applyfull-time25 days ago

About The Role

Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience.

Now we look for a Data Scientist to join our ML team

Job Responsibilities

  • Machine Learning & Modeling
  • Develop and train machine learning models for prediction, classification.
  • Build and evaluate regression, classification, clustering, and time-series models.
  • Design feature engineering pipelines and data preprocessing workflows.
  • Evaluate model performance, robustness, and production readiness.
  • Deploy and maintain ML models in collaboration with ml-ops teams.
  • Data Analysis & Exploration
  • Explore large datasets to identify patterns, trends, and hidden relationships.
  • Perform statistical analysis and hypothesis testing.
  • Distillate open-source datasets by proprietary data via LLM agents
  • Detect anomalies, outliers, and unexpected metric movements.
  • Translate business or product questions into analytical tasks.
  • Data Pipelines & Infrastructure
  • Work with data pipelines and streaming data systems.
  • Process and transform large datasets using Python and SQL.
  • Work with event streams and messaging systems (Kafka).
  • Contribute to data quality monitoring and dataset validation.
  • Work with analytical databases and data warehouses.
  • Model Monitoring & Experimentation
  • Design experiments and evaluate model performance in real environments.
  • Implement monitoring for model performance and data drift.
  • Support A/B testing and experimentation frameworks.
  • Improve models based on production feedback and metrics.
  • Cross‑Functional Collaboration
  • Work closely with ML engineers, data engineers, and product teams.
  • Communicate model results and analytical insights clearly.
  • Contribute to the development of ML best practices within the team

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