Job Location: Bangalore/Bengaluru
- 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.
Value you will deliver
- 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
Our ideal candidate comes with
- 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
- 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
- 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
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