Senior Data Scientist / Machine Learning Engineer
Astro Sirens LLC
contract
Posted on:
Location Type: Remote
Location: Ukraine
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Job Level
Tech Stack
About the role
- 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
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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdata processingPythonscikit-learnTensorFlowPyTorchXGBoostSQLMLOpsbig data
Soft Skills
communicationcollaborationmentoringproblem-solvinganalytical thinkingadaptabilityleadershipinsight translationstakeholder engagementbest practices adherence
Certifications
Bachelor’s degreeMaster’s degree