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Company | Veridic Solutions |
Address | Bellevue, WA, United States |
Employment type | CONTRACTOR |
Salary | |
Expires | 2023-09-01 |
Posted at | 9 months ago |
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.
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.
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