What are the responsibilities and job description for the Data Engineer position at Virtusa?
Description
Job Description : - Data Analysis & Preprocessing : Analyze large datasets, clean and preprocess data for modeling, and derive actionable insights.
Model Development : Design, develop, and implement machine learning models to solve complex business problems.
Algorithm Optimization : Optimize and tune models to improve performance and scalability.
Data Pipeline Development : Develop and maintain scalable data pipelines for data extraction, transformation using Kedro.
Collaboration : Work closely with data engineers, analysts, and software developers to integrate models into production systems.
Documentation : Prepare detailed documentation of workflows, methodologies, and results for future reference and reproducibility.
Monitoring & Evaluation : Continuously monitor the performance of deployed models and improve them over time.
Oracle SQL Queries : Write oracle queries and perform data analysis in tables by executing multiple queries
Responsibilities :
Data Analysis & Preprocessing : Analyze large datasets, clean and preprocess data for modeling, and derive actionable insights.
Model Development : Design, develop, and implement machine learning models to solve complex business problems.
Algorithm Optimization : Optimize and tune models to improve performance and scalability.
Data Pipeline Development : Develop and maintain scalable data pipelines for data extraction, transformation using Kedro.
Collaboration : Work closely with data engineers, analysts, and software developers to integrate models into production systems.
Documentation : Prepare detailed documentation of workflows, methodologies, and results for future reference and reproducibility.
Monitoring & Evaluation : Continuously monitor the performance of deployed models and improve them over time.
Oracle SQL Queries : Write oracle queries and perform data analysis in tables by executing multiple queries
Required Skills :
Python Programming : Strong proficiency in Python, with experience in libraries such as NumPy, Pandas, Scikit-learn, Transformer , TensorFlow, and PyTorch.
Machine Learning : Experience building and deploying machine learning models, including supervised and familiarity with algorithms like regression, decision trees, clustering, and deep learning.
SQL : Expertise in writing and optimizing complex SQL queries to extract and manipulate data from relational databases.
Data Wrangling : Experience in data manipulation, data cleaning, and transformation.
Model Evaluation : Ability to evaluate model performance using metrics such as accuracy, precision, recall, F1-score, and AUC-ROC.
Data Visualization : Proficiency in data visualization tools such as Matplotlib, Seaborn, and Plotly for reporting insights.
Version Control : Experience with Git or other version control systems for collaborative development.
API Development : Experience with REST APIs and deploying machine learning models as microservices
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