Altimetrik | is Hiring | ER – Data Science | BigDataKB.com | 06-04-22

• Ability to understand codes written by data scientists and modularize the same.

• Ability perform machine learning data preprocessing activities including data extraction, data validation, model building, model training and model validation.

• Understand existing R-based models (mainly classification, forecasting models) and re-engineer them in Python/Sagemaker for better accuracy.

• Perform data preprocessing operations on large dataset like

• Missing Data Imputation, Outlier Treatment

• Scaling, Normalization, Standardization

• Encoding for Categorical Variables

• OversamplingUnder-sampling for reducing class imbalance

• Feature encoding

• Feature transformation

• Feature engineering

• Building ML models using python/R data science libraries.

• Model performance tuning with hyper parameters.

• Ability to learn and pick up a new language/tool/ platform quickly.

• Evaluate and maintain various Machine Learning models and ability to run Machine Learning models on huge amount of data.

• Build reusable code for faster turnaround time to business problem solving.

• Achieve top line and bottom line targets for the account/portfolio

• Detailed account plan and achieving on the same on a quarter on quarter basis

• Formal engagement plan for liaising with key senior customer stakeholders, and facilitating Altimetrik leadership connects with client executives via a multi-tier approach

• Lead and influence an engaged and effective workforce and that is fully integrated with Altimetrik vision, values and purpose

• 3-7 Years of experience working as a Data Scientist/machine learning engineer to build AI/ML models.

• Strong experience in implementing AI/ML models using any one of the programming languages Python or R. Knowledge in both will be a great plus.

• Experience building in Regression and Time Series models like ARIMA, SARIMA, tbats, prophet, glm, xgboost etc.

• Experience in common python data science libraries such as Pandas, Scikit, NumPy, matplotlib, seaborn etc. Or, experience in R data science libraries such as dplyr, tidyr, stats, zoo,ggplot2, caret, shiny, forecast, plotly, lattice etc.

• Experience in using tools like Pycharm, R-studio, Spider and Jpyter notebook, Jira and confluence.

• Strong exposure to end to end Machine learning life cycle process like data preprocessing, model building, model evaluation and model deployment.

• Knowledge in AWS Sagemaker and Sagemaker ML pipeline.

• Good exposer to standard coding practices and experience in writing robust, reusable and manageable code.

• Good foundation on statistics skills, such as distributions, statistical testing, regression, etc.

• Knowledge and experience in model performance tuning and model validation with different metrics MSE, forecast error/bias, R-Square, Adjusted R-square, MAPE, F1 score etc.

• Proficiency in Agile methodology, scrum ceremonies, usage of Jira and Confluence

Technical/Functional competency

• IT software development, digital solutions, digital transformation background is mandatory.

• Good understanding of technology, software development methodologies especially as relating to developing custom software for customers using agile principles

Behavioral competency

• Strong problem solving skills

• Ability to lead initiatives and people toward common goals

• Working knowledge of systems infrastructure

• Excellent oral and written communication, presentation, and analytical skills