Data Scientist
2 weeks ago
- 3-5 years of hands-on experience in building machine learning systems for large datasets.
- Ability to break down and frame business problems into data science solutions and hands-on capability to create MVP out of it and run a DS project end to end independently.
- In-depth knowledge on supervised and unsupervised machine learning algorithms including classification, clustering, and regression.
- Experience in NLP (Sequence segmentation, Labeling and parsing, Knowledge extraction, Question answering, Multi text learning, ontology, taxonomy building), Machine Learning.
- Experience in Entity Extraction, Entity Linking, Clustering algorithms.
- Proficient in Math & Deep Learning (VAE, RNN, LSTM, CNN, attention models, Transfomer etc.), machine learning(svm, random forest), Clustering, topic modeling(LDA, LSA) and graph models.
- Experience in Python, Scikit-learn, Pytorch, Keras, Tensorflow
- Experience of implementing Deep Learning models into production
- Familiarity with distributed computing.
- Experience with SQL and/or No-SQL modelling.
- Excellent communication, analytical and problem-solving skills.
- B.S./B.S.E./MS degree in Applied Math, Data Science, Computer Science, Physics, or Similar Technical Field
- Passion to dive deep to resolve problems at their root.
- Experience in Data Governance, Data quality, Model Governance & MLops is a huge plus. Functional knowledge of platforms such as MLFLOW, Hopsworks/Sagemaker feature store/feast/Tecton, Seldon, DVC.
- Experience on building fair & explainable ML based product.
- Experience on federated learning, differential privacy, reinforcement learning.
- Experience on A/B testing, federated learning, differential privacy.
- Experience of git, flask, restful APIs.
- Experience working in a fast-paced, high tech environment.
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