Role: Sr. AI ML Engineer / Data Scientist
Location: Bellevue,WA
Mandatory Skills • PySpark, Python and machine learning libraries like numpy, pandas, sci-kit-learn.
• Machine Learning Algorithms Like Linear Regression, Logistic Regression, K-Nearest Neighbour, Navie Bayes, Decision Tree, SVM, MLP, PCA, LDA, K-mean, Isolation Forest, DBSCAN, Ensemble Machine Learning Algorithm (Random Forest, Adaboost, Xg-Boost etc).
• Deep Learning Models, Generative Adversarial Network (GAN), Reinforcement Learning Models (SARSA, Q-Learning), LSTM, BI-LSTM, BERT, GPT-3, GPT-4, Transformers.
• Natural Language Processing, NER Models, have knowledge in OpenAI , Image Processing.
---------------
Job Description :
We are searching for a strategic and inquisitive senior data scientist/senior AI-ML Engineer to develop and run with data-centred projects in telecom sector.
KEY RESPONSIBILITIES:
• Formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests (telecom-domain).
• Collating and cleaning data from various entities .
• Selecting and employing advanced statistical procedures to obtain actionable insights.
• Cross-validating models to ensure their generalizability.
• Producing and disseminating non-technical reports that detail the successes and limitations of each project.
• Suggesting ways in which insights obtained might be used to inform business strategies.
• Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant.
Required Skills : (+9 years )
• Advanced degree in data science, statistics, computer science, or similar.
• Industry experience as data scientist and experience in machine learning, data visualizations, data mining, data understanding.
• Hands-on experience in PySpark, Python and machine learning libraries like numpy, pandas, sci-kit-learn,
• Should have sound knowledge in both Supervised and Unsupervised Machine Learning Algorithms Like Linear Regression, Logistic Regression, K-Nearest Neighbor, Navie Bayes, Decision Tree, SVM, MLP, PCA, LDA, K-mean, Isolation Forest, DBSCAN, Ensemble Machine Learning Algorithm (Random Forest, Adaboost, Xg-Boost etc).
• Should have knowledge in Statistics, hypothesis testing, EDA, Feature Engineering etc.
• Should have experience in Deep Learning Models, Generative Adversarial Network (GAN), Reinforcement Learning Models (SARSA, Q-Learning), LSTM, BI-LSTM, BERT, GPT-3, GPT-4, Transformers.
• Experience in Natural Language Processing, NER Models, have knowledge in OpenAI , Image Processing.
• Knowledge in Time-series Forecasting , Predictive Methodologies.
• Proficiency in Python, PySpark, Hive datasets.
• In-depth understanding of SQL, NoSQL.
• Competent in machine learning principles and techniques.
• Demonstrable history of devising and overseeing data-centered projects.
• Knowledge in Clean Code and code-optimization.
• Compliance with prevailing ethical standards.
• Good to have experience in cloud environment (AWS, Azure )etc.
• Research and innovation.
-- Location: Bellevue,WA
Mandatory Skills • PySpark, Python and machine learning libraries like numpy, pandas, sci-kit-learn.
• Machine Learning Algorithms Like Linear Regression, Logistic Regression, K-Nearest Neighbour, Navie Bayes, Decision Tree, SVM, MLP, PCA, LDA, K-mean, Isolation Forest, DBSCAN, Ensemble Machine Learning Algorithm (Random Forest, Adaboost, Xg-Boost etc).
• Deep Learning Models, Generative Adversarial Network (GAN), Reinforcement Learning Models (SARSA, Q-Learning), LSTM, BI-LSTM, BERT, GPT-3, GPT-4, Transformers.
• Natural Language Processing, NER Models, have knowledge in OpenAI , Image Processing.
---------------
Job Description :
We are searching for a strategic and inquisitive senior data scientist/senior AI-ML Engineer to develop and run with data-centred projects in telecom sector.
KEY RESPONSIBILITIES:
• Formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests (telecom-domain).
• Collating and cleaning data from various entities .
• Selecting and employing advanced statistical procedures to obtain actionable insights.
• Cross-validating models to ensure their generalizability.
• Producing and disseminating non-technical reports that detail the successes and limitations of each project.
• Suggesting ways in which insights obtained might be used to inform business strategies.
• Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant.
Required Skills : (+9 years )
• Advanced degree in data science, statistics, computer science, or similar.
• Industry experience as data scientist and experience in machine learning, data visualizations, data mining, data understanding.
• Hands-on experience in PySpark, Python and machine learning libraries like numpy, pandas, sci-kit-learn,
• Should have sound knowledge in both Supervised and Unsupervised Machine Learning Algorithms Like Linear Regression, Logistic Regression, K-Nearest Neighbor, Navie Bayes, Decision Tree, SVM, MLP, PCA, LDA, K-mean, Isolation Forest, DBSCAN, Ensemble Machine Learning Algorithm (Random Forest, Adaboost, Xg-Boost etc).
• Should have knowledge in Statistics, hypothesis testing, EDA, Feature Engineering etc.
• Should have experience in Deep Learning Models, Generative Adversarial Network (GAN), Reinforcement Learning Models (SARSA, Q-Learning), LSTM, BI-LSTM, BERT, GPT-3, GPT-4, Transformers.
• Experience in Natural Language Processing, NER Models, have knowledge in OpenAI , Image Processing.
• Knowledge in Time-series Forecasting , Predictive Methodologies.
• Proficiency in Python, PySpark, Hive datasets.
• In-depth understanding of SQL, NoSQL.
• Competent in machine learning principles and techniques.
• Demonstrable history of devising and overseeing data-centered projects.
• Knowledge in Clean Code and code-optimization.
• Compliance with prevailing ethical standards.
• Good to have experience in cloud environment (AWS, Azure )etc.
• Research and innovation.
Best Regards, | ||||||||||||||
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