Data Scientist - Core Analytics Associate

Role Overview: You have an exciting opportunity to join the Data Analytics team as a Data Scientist - Core Analytics Associate at a dynamic and growing company. In this role, you will lead the data strategy, apply advanced statistical techniques, and develop machine learning models to drive business value and competitive advantage. Key Responsibilities: - Lead Data Strategy: Define and execute the data strategy, identify opportunities for leveraging data, and drive business value. - Apply Advanced Statistical Techniques: Utilize predictive modeling, time series analysis, and optimization algorithms to extract insights from complex data sets. - Develop Machine Learning Models: Create models for customer segmentation, churn prediction, recommendation systems, and anomaly detection. - Cross-functional Collaboration: Work closely with cross-functional teams to identify business problems, design solutions, and drive implementation. - Model Deployment and Monitoring: Implement machine learning models into scalable environments and establish monitoring processes. - Mentorship and Leadership: Provide guidance to junior data scientists, promote best practices, and contribute to team development. - Continuous Learning: Stay updated with the latest trends in data science and actively seek opportunities to enhance skills and knowledge. Qualification Required: - Masters or Ph.D. degree in Data Science, Computer Science, Statistics, Mathematics, or related field. - Minimum 8 years of experience in data science and data engineering. - Proficiency in programming languages such as Python or R, data manipulation libraries like Pandas and NumPy, and machine learning frameworks like TensorFlow or PyTorch. - Deep Understanding of AI/ML Techniques: Hands-on experience with various AI/ML algorithms and techniques. - Experience with big data technologies such as Apache Spark, Hadoop, and SQL or NoSQL databases. - Strong data visualization and communication skills using tools like Matplotlib, Seaborn, Plotly, or Tableau. - Business Acumen: Ability to understand business problems and deliver actionable recommendations. Additional Company Details: JPMorgan Chase & Co. is a leading financial institution offering innovative financial solutions to consumers, businesses, and institutional clients. With a history spanning over 200 years, the company is a leader in investment banking, consumer banking, commercial banking, and asset management. J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions, providing expertise in asset classes and wealth management strategies. The company values diversity and inclusion, making accommodations for employees' needs and beliefs. (Note: The job description does not provide specific details about the company beyond what is mentioned above.) Role Overview: You have an exciting opportunity to join the Data Analytics team as a Data Scientist - Core Analytics Associate at a dynamic and growing company. In this role, you will lead the data strategy, apply advanced statistical techniques, and develop machine learning models to drive business value and competitive advantage. Key Responsibilities: - Lead Data Strategy: Define and execute the data strategy, identify opportunities for leveraging data, and drive business value. - Apply Advanced Statistical Techniques: Utilize predictive modeling, time series analysis, and optimization algorithms to extract insights from complex data sets. - Develop Machine Learning Models: Create models for customer segmentation, churn prediction, recommendation systems, and anomaly detection. - Cross-functional Collaboration: Work closely with cross-functional teams to identify business problems, design solutions, and drive implementation. - Model Deployment and Monitoring: Implement machine learning models into scalable environments and establish monitoring processes. - Mentorship and Leadership: Provide guidance to junior data scientists, promote best practices, and contribute to team development. - Continuous Learning: Stay updated with the latest trends in data science and actively seek opportunities to enhance skills and knowledge. Qualification Required: - Masters or Ph.D. degree in Data Science, Computer Science, Statistics, Mathematics, or related field. - Minimum 8 years of experience in data science and data engineering. - Proficiency in programming languages such as Python or R, data manipulation libraries like Pandas and NumPy, and machine learning frameworks like TensorFlow or PyTorch. - Deep Understanding of AI/ML Techniques: Hands-on experience with various AI/ML algorithms and techniques. - Experience with big data technologies such as Apache Spark, Hadoop, and SQL or NoSQL databases. - Strong data visualization and communication skills using tools like Matplotlib, Seaborn, Plotly, or Tableau. - Business Acumen: Ability to understand business problems and deliver actionable recommendations. Addit