Data Scientist with Machine Learning

As a Data Scientist in our company, your role will involve extracting and analyzing data from company databases to drive product development and marketing strategies. You will be responsible for analyzing large datasets to uncover trends, patterns, and insights that can influence business decisions. Leveraging predictive and AI/ML modeling techniques, you will enhance customer experience, boost revenue generation, improve ad targeting, and more. Your tasks will include designing, implementing, and optimizing machine learning models for various applications such as predictive analytics, natural language processing, and recommendation systems. You will also conduct experiments to fine-tune machine learning models and deploy them into production environments, ensuring scalability. Key Responsibilities: - Extract and analyze data from company databases to optimize product development and marketing strategies. - Analyze large datasets to uncover trends, patterns, and insights for business decisions. - Utilize predictive and AI/ML modeling techniques to enhance customer experience and boost revenue. - Design, implement, and optimize machine learning models for various applications. - Conduct experiments to fine-tune machine learning models and evaluate their performance. - Deploy machine learning models into production environments, ensuring scalability. Qualifications: - Bachelors, Masters, or Ph.D in Computer Science, Data Science, Mathematics, Statistics, or a related field. - 2 years of experience in Analytics, Machine Learning, and Deep Learning. - Proficiency in Python and familiarity with machine learning libraries (e.g., Numpy, Pandas, TensorFlow, Keras, PyTorch, Scikit-learn). - Strong experience in data wrangling, cleaning, and transforming raw data. - Hands-on experience in developing, training, and deploying machine learning models. - In-depth understanding of machine learning algorithms and their appropriate use cases. - Experience with model evaluation techniques and cloud platforms (AWS, GCP, Azure). - Proficiency in data processing and manipulation techniques. - Excellent problem-solving skills and strong communication skills. Good To Have: - Experience in the banking/financial services or industry-specific sector. - Familiarity with cloud-based machine learning platforms such as Azure, AWS, or GCP. As a Data Scientist in our company, your role will involve extracting and analyzing data from company databases to drive product development and marketing strategies. You will be responsible for analyzing large datasets to uncover trends, patterns, and insights that can influence business decisions. Leveraging predictive and AI/ML modeling techniques, you will enhance customer experience, boost revenue generation, improve ad targeting, and more. Your tasks will include designing, implementing, and optimizing machine learning models for various applications such as predictive analytics, natural language processing, and recommendation systems. You will also conduct experiments to fine-tune machine learning models and deploy them into production environments, ensuring scalability. Key Responsibilities: - Extract and analyze data from company databases to optimize product development and marketing strategies. - Analyze large datasets to uncover trends, patterns, and insights for business decisions. - Utilize predictive and AI/ML modeling techniques to enhance customer experience and boost revenue. - Design, implement, and optimize machine learning models for various applications. - Conduct experiments to fine-tune machine learning models and evaluate their performance. - Deploy machine learning models into production environments, ensuring scalability. Qualifications: - Bachelors, Masters, or Ph.D in Computer Science, Data Science, Mathematics, Statistics, or a related field. - 2 years of experience in Analytics, Machine Learning, and Deep Learning. - Proficiency in Python and familiarity with machine learning libraries (e.g., Numpy, Pandas, TensorFlow, Keras, PyTorch, Scikit-learn). - Strong experience in data wrangling, cleaning, and transforming raw data. - Hands-on experience in developing, training, and deploying machine learning models. - In-depth understanding of machine learning algorithms and their appropriate use cases. - Experience with model evaluation techniques and cloud platforms (AWS, GCP, Azure). - Proficiency in data processing and manipulation techniques. - Excellent problem-solving skills and strong communication skills. Good To Have: - Experience in the banking/financial services or industry-specific sector. - Familiarity with cloud-based machine learning platforms such as Azure, AWS, or GCP.