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Senior Data Scientist / Machine Learning Engineer
Location
Ukraine
Posted
62 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Scientist / Machine Learning Engineer
Astro Sirens LLC
• Design, develop, and deploy machine learning models for real-world production use cases • Analyze large and complex datasets to extract insights that inform model development and optimization • Build end-to-end ML pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment • Collaborate with data engineers, software engineers, product managers, and business stakeholders to define machine learning requirements • Implement model monitoring, performance tracking, and retraining strategies • Optimize models for scalability, performance, and reliability in cloud-based environments • Ensure data quality, reproducibility, and adherence to best practices in ML development • Translate machine learning outcomes into clear, actionable insights for technical and non-technical audiences • Contribute to improving ML standards, tools, and best practices across teams • Mentor junior data scientists and machine learning engineers
Job Requirements
- Bachelor’s or Master’s degree in Data Science, Machine Learning, Computer Science, Statistics, or a related field
- 5+ years of experience in data science, machine learning, or applied AI roles
- Strong proficiency in Python for data processing and machine learning
- Hands-on experience with machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost)
- Strong understanding of supervised and unsupervised learning, deep learning, and model evaluation techniques
- Expertise in SQL and experience with relational databases (PostgreSQL, MySQL, MS SQL)
- Experience deploying machine learning models into production environments
- Familiarity with MLOps practices (model versioning, CI/CD, monitoring, retraining)
- Experience with cloud platforms such as AWS, GCP, or Azure
- Understanding of data governance, model ethics, and data privacy considerations
- Strong communication skills with the ability to work effectively with U.S.-based stakeholders
- Preferred Qualifications
- Experience with big data technologies (Spark, Hadoop, or similar)
- Knowledge of Docker, Kubernetes, and containerized ML workflows
- Experience supporting ML systems at scale
Benefits
- Paid Time Off (PTO)
- Work From Home
- Professional development opportunities
- Training & Development Programs
- Collaborative and inclusive company culture
- Competitive salary and performance-based bonuses
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