Data Scientist Machine Learning Engineer

• Collect and prepare raw email traffic and customer-reported samples across multiple languages.
• Normalize and translate multilingual datasets into a common format suitable for model training.
• Build reproducible data preparation and machine learning pipelines.
• Train and fine-tune machine learning classifiers using labeled datasets.
• Conduct experimentation and optimize model performance.
• Evaluate models using holdout datasets and detailed performance analysis.
• Analyze false positives and false negatives and identify opportunities for improvement.
• Perform language-specific quality checks and overall model validation.
• Document project methodology, progress, experiments, and results throughout the engagement.
• Work closely with the client to deliver a validated model ready for production deployment.

The ideal candidate will combine strong data preparation and engineering skills with hands-on experience in machine learning, supervised classification, model training, and evaluation. Experience working with NLP and multilingual datasets is highly desirable., * Strong experience in Data Science and/or Machine Learning Engineering.

• Strong data engineering and data preparation experience, particularly with collection, normalization, and transformation of datasets.
• Hands-on experience with machine learning model training, tuning, and experimentation.
• Experience evaluating classifier performance and conducting false-positive/false-negative analysis.
• Experience building reproducible ML workflows and pipelines.
• Ability to clearly document technical methodology, progress, and results.
• Strong analytical and problem-solving skills.

Nice to Have

• Experience with NLP (Natural Language Processing).
• Experience working with multilingual datasets.
• Experience with supervised classification workflows.
• Experience working with email data or similar text-based datasets.