Data Scientist

Description

• The resource should be good at ML, JAVA and Python script.
• Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world

Responsibilities

• • Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• • Managing available resources such as hardware, data, and personnel so that deadlines are met
• • Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability
• • Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• • Verifying data quality, and/or ensuring it via data cleaning
• • Supervising the data acquisition process if more data is needed
• • Finding available datasets online that could be used for training
• • Defining validation strategies
• • Defining the preprocessing or feature engineering to be done on a given dataset
• • Defining data augmentation pipelines Training models and tuning their hyperparameters
• • Analyzing the errors of the model and designing strategies to overcome them
• • Deploying models to production