Senior Data Scientist - R/Python

As a Senior Data Scientist, you will play a crucial role in analyzing data sets from various products, identifying patterns, and converting raw data into valuable insights for enterprises. Your responsibilities will include developing custom data models, evaluating new data sources, collaborating with cross-functional teams, and monitoring model performance. Key Responsibilities: - Analyze data sets from different products to identify patterns. - Transform raw data into actionable insights for business improvement. - Evaluate the accuracy of new data sources and gathering techniques. - Develop custom data models and algorithms for data analysis. - Collaborate with cross-functional teams to implement models and monitor outcomes. - Create processes and tools to monitor model performance and data accuracy. Qualifications: - Strong problem-solving skills with a focus on product development. - Eagerness to learn and master new technologies and techniques. - Proficiency in statistical computer languages such as R and Python. - Experience working with various data architectures. - Knowledge of statistical and data mining techniques. - Familiarity with machine learning techniques and their practical advantages and drawbacks. - Prior experience in zero-touch solutions is advantageous. - 3-5 years of experience in manipulating data sets and building statistical models. - Bachelor's or Master's degree in computer science or a related quantitative field. - Proficiency in Python, R, and data science toolkits like Jupyter, Pandas, Numpy, Scikit-learn, TensorFlow, Keras. - Experience in statistical techniques such as GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis. - Familiarity with various types of databases, including RDBMS, Graph, No-SQL. As a Senior Data Scientist, you will play a crucial role in analyzing data sets from various products, identifying patterns, and converting raw data into valuable insights for enterprises. Your responsibilities will include developing custom data models, evaluating new data sources, collaborating with cross-functional teams, and monitoring model performance. Key Responsibilities: - Analyze data sets from different products to identify patterns. - Transform raw data into actionable insights for business improvement. - Evaluate the accuracy of new data sources and gathering techniques. - Develop custom data models and algorithms for data analysis. - Collaborate with cross-functional teams to implement models and monitor outcomes. - Create processes and tools to monitor model performance and data accuracy. Qualifications: - Strong problem-solving skills with a focus on product development. - Eagerness to learn and master new technologies and techniques. - Proficiency in statistical computer languages such as R and Python. - Experience working with various data architectures. - Knowledge of statistical and data mining techniques. - Familiarity with machine learning techniques and their practical advantages and drawbacks. - Prior experience in zero-touch solutions is advantageous. - 3-5 years of experience in manipulating data sets and building statistical models. - Bachelor's or Master's degree in computer science or a related quantitative field. - Proficiency in Python, R, and data science toolkits like Jupyter, Pandas, Numpy, Scikit-learn, TensorFlow, Keras. - Experience in statistical techniques such as GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis. - Familiarity with various types of databases, including RDBMS, Graph, No-SQL.