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Senior Data Scientist
Posted 4 days agoViewed
💎 Seniority level: Senior, 7+ years
📍 Location: Hong Kong, Macao
🔍 Industry: Software Development
🏢 Company: Intellectsoft👥 251-500Augmented RealityArtificial Intelligence (AI)DevOpsBlockchainInternet of ThingsUX DesignWeb DevelopmentMobile AppsQuality AssuranceSoftware
⏳ Experience: 7+ years
Requirements:
- 7+ years of experience in data science, machine learning, and statistical modeling.
- Strong programming skills in Python, SQL, and Spark.
- Hands-on experience with MLflow, PyTorch, Spark MLlib, and FastAPI for model development and deployment.
- Understanding of distributed computing and big data processing using Apache Spark and ClickHouse.
- Proficiency in feature engineering, data preprocessing, and model tuning for large-scale datasets.
- Experience in building and deploying ML models in production environments using TorchServe, FastAPI, or similar frameworks.
- Knowledge of deep learning architectures (CNNs, RNNs, transformers) and their practical applications.
- Strong grasp of MLOps best practices, including CI/CD for ML models, model monitoring, and retraining pipelines.
- Understanding of real-time analytics and event-driven architectures for processing streaming data.
- Experience working with SQL and NoSQL databases such as PostgreSQL, ClickHouse, and Delta Lake.
- Strong ability to collaborate with data engineers, architects, and business analysts to ensure ML models align with business objectives.
- Knowledge of A/B testing methodologies and causal inference techniques for evaluating model effectiveness.
- Familiarity with cloud services (AWS, GCP, or Azure) for scalable model training and deployment.
Responsibilities:
- Design the architecture for the open-source-based data analytics platform.
- Develop scalable data models, data pipelines, and data lakes.
- Ensure integration of various data sources, including Kafka, NiFi, Apache Airflow, and Spark.
- Implement modern data platform components like Apache Iceberg, Delta Lake, ClickHouse, and PostgreSQL.
- Define and enforce data governance, security, and compliance best practices.
- Optimize data storage, access, and retrieval for performance and scalability.
- Collaborate with data scientists, engineers, and business analysts to ensure platform usability.
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