Data Scientist/Machine Learning Engineer

As a Python and Machine Learning Developer at our company, you will play a crucial role in designing, building, and implementing credit risk models. You will be responsible for interacting with clients to understand their requirements and brainstorming solutions. Your expertise in Python, ML, and banking model development will be essential in contributing insights that align with business objectives. With 3+ years of experience in predictive modeling, you will create innovative data and machine learning solutions while collaborating with various stakeholders. Key Responsibilities: - Design, implement, test, deploy, and maintain data and machine learning solutions - Collaborate with product managers and stakeholders to solve business problems - Analyze large datasets to identify trends and risk factors - Utilize advanced statistical methods to build robust models - Stay updated with the latest methodologies and tools in credit risk modeling Qualifications Required: - 3+ years of experience in Python, ML, and banking model development - Hands-on experience with predictive modeling and machine learning - Proficiency in Python, Logistic Regression, Artificial Intelligence, and Natural Language Processing - Familiarity with Fraud Detection, Deep Learning, Scikit-Learn, Numpy, Pandas, and Statistical Modeling You will also have the opportunity to work on unstructured data, such as text, and collaborate with data scientists and business analysts to align models with business needs. Continuous improvement and staying updated with the latest advancements in credit risk modeling and R programming will be crucial in this role. If you possess a passion for data science, machine learning, and model development, and are looking to work in a dynamic environment where your skills are valued and challenged, then we encourage you to apply for this exciting opportunity. As a Python and Machine Learning Developer at our company, you will play a crucial role in designing, building, and implementing credit risk models. You will be responsible for interacting with clients to understand their requirements and brainstorming solutions. Your expertise in Python, ML, and banking model development will be essential in contributing insights that align with business objectives. With 3+ years of experience in predictive modeling, you will create innovative data and machine learning solutions while collaborating with various stakeholders. Key Responsibilities: - Design, implement, test, deploy, and maintain data and machine learning solutions - Collaborate with product managers and stakeholders to solve business problems - Analyze large datasets to identify trends and risk factors - Utilize advanced statistical methods to build robust models - Stay updated with the latest methodologies and tools in credit risk modeling Qualifications Required: - 3+ years of experience in Python, ML, and banking model development - Hands-on experience with predictive modeling and machine learning - Proficiency in Python, Logistic Regression, Artificial Intelligence, and Natural Language Processing - Familiarity with Fraud Detection, Deep Learning, Scikit-Learn, Numpy, Pandas, and Statistical Modeling You will also have the opportunity to work on unstructured data, such as text, and collaborate with data scientists and business analysts to align models with business needs. Continuous improvement and staying updated with the latest advancements in credit risk modeling and R programming will be crucial in this role. If you possess a passion for data science, machine learning, and model development, and are looking to work in a dynamic environment where your skills are valued and challenged, then we encourage you to apply for this exciting opportunity.