Job Description

• 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.
• 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