Data Science & Engineering Lead

📋 Description

• Design and implement supervised and unsupervised ML models for business problems.
• Lead neural networks (ANN, CNN, Transformer, GAN, RNN) development.
• Build scalable data pipelines for streaming and batch workloads.
• Architect lakehouse solutions using Delta/Iceberg architectures.
• Lead ETL development with Airflow, DBT, Airbyte.
• Oversee MLOps pipelines for production using SageMaker, Databricks, and Azure ML Studio.

🎯 Requirements

• Proficient with TensorFlow, PyTorch; CNN, GAN, Transformers.
• Hands-on with Scikit-learn, Pandas, NumPy.
• MLOps: SageMaker, Databricks, Azure ML Studio.
• Spark/Glue/EMR for distributed training.
• ETL pipelines: Airflow, DBT, Airbyte.
• Lakehouse: Delta/Iceberg; Great Expectations.
• Cloud: AWS or Azure; IAM, VPC, Lambda, Kinesis, Kafka.
• Bachelor's degree required; Master/PhD preferred.

🎁 Benefits

• Competitive benefits.
• Collaborative culture.