3 - 8 years
10 - 20 Lacs
Posted:1 month ago|
Platform:
Work from Office
Full Time
- Bachelors or Master’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
- Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus.
- Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer).
- ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. - Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. - Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. - MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). - Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing.
- Experience with Graph ML, reinforcement learning, or causal inference modeling.
- Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. - Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. - Experience with distributed computing frameworks (Spark, Dask, Ray).
Ugam
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