Principal Architect
1 week ago
More like ML Engineer with Python, ML techniques like Timeseries, Regression, Clustering, Classification, SQL
**Role**:Principal Architect - Applied Machine Learning
**Experience**: 10+ years
**Work location**: India
- What You'll Do:
- Build and train production-grade ML models on large-scale datasets to solve various business use cases for Supply Chain.-
- Use large-scale data processing frameworks for feature engineering and be proficient across various data both structured and un-structured.-
- Use Deep Learning models like CNN, RNN and NLP (BERT) for solving various business use cases like name entity resolution, forecasting and anomaly detection.-
- Ability to build ML models across Public and Private clouds including container-based Kubernetes environments. You will collaborate to develop large-scale data modeling experiments, evaluating against strong baselines, and extracting key statistical insights and/or cause and effect relations.
**Basic Qualifications**:
- Advanced Degree in field of Computer Science, Data Science or equivalent discipline.-
- Minimum 5+ years of working experience as a data scientist-
- Expertise with Python, PySpark, DL frameworks like TensorFlow and MLOps.-
- Experience in designing and building highly scalable distributed ML models in production (Scala, applied machine learning, proficient in statistical methods, algorithms)-
- Experience with analytics (ex: SQL, Presto, Spark, Python, AWS suite). Awareness of the same in GCP would be a plus.-
- Experience with machine learning techniques and advanced analytics (e.g. regression, classification, clustering, time series, econometrics, causal inference, mathematical optimization)- Experience working with end-to-end pipelines using frameworks like KubeFlow, TensorFlow and/or crowd-sourced data labeling a plus
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