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• Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python.
• Demonstrable competency in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
• Must have experience in dealing with outliers, denoising data and handling the impact of pandemic like situations.
• Should be able to perform EDA of raw data & feature engineering wherever applicable.
• Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
• Should be able to leverage cloud platforms for training and deploying large scale solutions.
• Should be able to train and evaluate ML model using various machine learning and deep learning algorithm. • Retrain and maintain model accuracy in deployment.
• Should be able to package & deploy large scale models on on-premise systems using multiple approaches including docker.
• Should be able to take complete ownership of the assigned project.
• Experience of working in Agile environments • Well versed with JIRA or equivalent project tracking tool.

Competencies /Skills

• Knowledge of cloud platforms (AWS, Azure and GCP).
• Exposure to No SQL databases (MongoDB, Cassandra, Cosmos DB, HBase).
• Forecasting experience in products like SAP, Oracle, Power BI, Qlik, etc.
• Proficiency in Excel (Power Pivot, Power Query, Macros, Charts).
• An experience with large data sets and distributed computing (Hive/Hadoop/Spark).
• Transfer learning using state of art models in different spaces vision, NLP and speech. - Integration with external services and Cloud API.
• Working with data annotation approaches and tools for text, images and videos