Job Description :
We are looking for a Data Scientist with strong expertise in Google Cloud Platform (GCP) to design and implement advanced data models and deploy scalable machine learning solutions. The ideal candidate will have a deep understanding of data science techniques and practical experience working with GCP’s suite of cloud services.
Key Responsibilities:
Data Science & Modeling:
Design and develop machine learning models for predictive analytics and decision support.
Apply advanced statistical, NLP, computer vision, and time series forecasting techniques.
Create and optimize data pipelines and ETL workflows for model training and deployment.
Cloud Implementation (GCP):
Deploy and manage ML models using Vertex AI, AI Platform, and BigQuery ML.
Build scalable data pipelines using Cloud Dataflow, Pub/Sub, and Cloud Composer (Airflow).
Use Google Cloud Storage, BigQuery, and Cloud Functions for data integration and management.
Collaboration & Strategy:
Collaborate with data engineers, cloud architects, and business teams to align models with business goals.
Translate complex data insights into actionable recommendations.
Ensure scalability, performance, and security of cloud-based data solutions.
Required Skills & Experience:
9+ years of experience in Data Science and Machine Learning.
3+ years of hands-on experience with GCP cloud services.
Strong knowledge of Python, SQL, and TensorFlow/PyTorch.
Proficient in BigQuery, Vertex AI, Cloud ML Engine, and Dataflow.
Experience with MLOps practices and tools like Kubeflow, MLflow, or CI/CD pipelines.
Solid understanding of cloud security, IAM, and service accounts.
Preferred Qualifications:
GCP Professional Data Engineer or Machine Learning Engineer certification.
Experience with APIs and microservices for model deployment.
Familiarity with Docker, Kubernetes, and CI/CD pipelines.
Knowledge of A/B testing, hyperparameter tuning, and model interpretability techniques.
Qualifications:
Bachelor’s degree in Computer Science, Information Technology, or a related field.
Screening Criteria:
Location:
Interview Details: