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| Job Location | Mumbai City |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | Banking / Financial Services |
| Functional Area | General / Operations Management |
| EmploymentType | Full-time |
Team DescriptionBusiness Intelligence team is part of Asset Management s Global Sales Enablement organization.The mission of the Business Intelligence ( BI ) team is to apply creativity, rigor, and data-driven thinking to help plan and execute the business growth of J.P. Morgan Asset Management. Our work is a blend of strategy, technology, data analysis, and execution with a key focus on defining data-driven distribution and marketing strategies for J.P. Morgan Asset Management.In this role, you will be expected to apply your marketing and data science background in order to make important contributions across a diverse array of projects. The role will require in-depth data manipulation, exploration, and analysis. We are a highly collaborative team - so you will have significant potential for learning and impact.Functional Responsibilities:Partnering with distribution stakeholders to identify opportunities for leveraging advanced analyticsBuilding analytical frameworks for marketing measurement A/B testing, campaign ROI, cost of acquisition modeling, lifetime value, etcIn-depth data exploration and data mining to develop a deep understanding of client behaviorContributing to and enhancing data models and feature storesLeveraging machine learning models and techniques to target opportunities and optimize processesDeveloping tools and solutions to measure model performance over timeFostering a data-driven, innovative cultureQualifications:Advanced degree in Statistics, Math, Engineering or other quantitative-focused field preferred3+ years experience with analytic techniques, statistical modeling and web analyticsExperience using computer languages (Python, Pyspark, etc.) to manipulate and analyze large datasetsProficient in Google AnalyticsKnowledge of variety of machine learning algorithms (linear regression, logistic regression, SVMs, Tree-based models, neural networks, etc.) and techniques (cross validation, feature selection approaches, hyper parameter optimization, missing data imputation etc.)Experience using machine learning libraries in Python (Sci-kit learn, tensorflow, etc.)Skills:A passion for technology, financial services and asset managementA balanced approach combining judgment, analytical rigor, curiosity, open-mindedness and creativityAbility to multi-task and manage competing priorities/workflowsProven ability to quickly learn the business, the application and adapt to ever changing prioritiesSelf-motivated, team player with strong work ethicAbility to build relationships across global teams,
Keyskills :
data sciencedata analysisasset managementmachine learningfinancial servicescomputer languagesab testing