Senior Data Scientist (Search)
9.0/10
Emerging Travel Group
$115,000 – $195,500 USD
Remote
senior
about 1 month ago
May be outdated
aianalyticstechPythonMLDLSQLPyTorchTensorFlowMLflowW&BDVC
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Description
What you'll do
- •Manage end-to-end ML projects: problem definition → solution → testing → deployment → support.
- •Work with data engineers to build datasets and define data requirements, and assess feasibility, risks, and constraints.
- •Work with data analysts to design and analyze A/B tests: metrics, splits, interpretation of results, and recommendations for deploying solutions.
- •Develop and train models (classic ML + DL), including solutions for text and image embeddings; conduct offline evaluation and error analysis.
- •Deploy the model and code to production (Python service), support releases and integrations.
- •Be responsible for model quality post-launch: metrics, monitoring, drift/degradation, improvement plans, and support procedures.
Conditions
- •Flexible schedules and opportunity to work remotely;
- •Ambitious and supportive team who love what they do, appreciate each other, and grow together;
- •Internal programs for adaptation and training, development of soft skills, and leadership abilities;
- •Partial compensation for participating in external training and conferences;
- •Corporate English school: Group and individual lessons, speaking clubs with colleagues from all over the world;
- •Corporate prices on hotels and travel services;
- •MyTime Day Off - an extra non-working day without loss of compensation.
Requirements
- •4+ years of experience as a Data Scientist (with specific experience in search / ranking / recommendations tasks).
- •Experience managing end-to-end ML projects in production (from setup to support).
- •Excellent understanding of classical ML: feature engineering, boosting, classification/regression, cross-validation, threshold selection, calibration.
- •Experience with DL (PyTorch/TensorFlow): understanding of fine-tuning principles and model inference.
- •Python (production-grade): readable code, tests for critical components, understanding of model/artifact packaging and service integration.
- •Understanding of ML monitoring: quality metrics, drift, alerts, diagnostics, and support procedures.
- •SQL proficiency sufficient for independent dataset building (joins, window functions).
- •Experience with model interpretability and error analysis.
- •MLflow / W&B / DVC or similar experiment tracking tools.
- •Orchestration/pipelines (Airflow/Prefect/Dagster) and advanced data processing.
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