Data Scientists ML

As a Data Science and Machine Learning specialist at Wholesale Bank, your role involves integrating new data sources, creating data models, developing data dictionaries, and building machine learning models. Your main objective is to design and deliver data products that assist squads at Wholesale Bank in achieving business outcomes and generating valuable business insights. You will be distinguishing between Data Analysts and Data Scientists within this job family. Key Responsibilities: - Extract and analyze data from company databases to drive the optimization and enhancement of product development and marketing strategies. - Analyze large datasets to uncover trends, patterns, and insights that can influence business decisions. - Leverage predictive and AI/ML modeling techniques to enhance and optimize customer experience, boost revenue generation, improve ad targeting, and more. - Design, implement, and optimize machine learning models for a wide range of applications such as predictive analytics, natural language processing, recommendation systems, and more. - Conduct experiments to fine-tune machine learning models and evaluate their performance using appropriate metrics. Qualifications: - Bachelors, Master's or Ph.D in Computer Science, Data Science, Mathematics, Statistics, or a related field. - 2+ years of experience in Analytics, Machine learning, Deep learning. - Proficiency in programming languages such as Python, and familiarity with machine learning libraries (e.g., Numpy, Pandas, TensorFlow, Keras, PyTorch, Scikit-learn). - Strong experience with data wrangling, cleaning, and transforming raw data into structured, usable formats. - Hands-on experience in developing, training, and deploying machine learning models for various applications (e.g., predictive analytics, recommendation systems, anomaly detection). - In-depth understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning) and their appropriate use cases. As a Data Science and Machine Learning specialist at Wholesale Bank, your role involves integrating new data sources, creating data models, developing data dictionaries, and building machine learning models. Your main objective is to design and deliver data products that assist squads at Wholesale Bank in achieving business outcomes and generating valuable business insights. You will be distinguishing between Data Analysts and Data Scientists within this job family. Key Responsibilities: - Extract and analyze data from company databases to drive the optimization and enhancement of product development and marketing strategies. - Analyze large datasets to uncover trends, patterns, and insights that can influence business decisions. - Leverage predictive and AI/ML modeling techniques to enhance and optimize customer experience, boost revenue generation, improve ad targeting, and more. - Design, implement, and optimize machine learning models for a wide range of applications such as predictive analytics, natural language processing, recommendation systems, and more. - Conduct experiments to fine-tune machine learning models and evaluate their performance using appropriate metrics. Qualifications: - Bachelors, Master's or Ph.D in Computer Science, Data Science, Mathematics, Statistics, or a related field. - 2+ years of experience in Analytics, Machine learning, Deep learning. - Proficiency in programming languages such as Python, and familiarity with machine learning libraries (e.g., Numpy, Pandas, TensorFlow, Keras, PyTorch, Scikit-learn). - Strong experience with data wrangling, cleaning, and transforming raw data into structured, usable formats. - Hands-on experience in developing, training, and deploying machine learning models for various applications (e.g., predictive analytics, recommendation systems, anomaly detection). - In-depth understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning) and their appropriate use cases.