Asset Management: Client Data Science - Associate
J.P. Morgan Asset Management (JPMAM) is committed to providing exceptional service to our clients and business partners. Our sales and client service teams, marketing support, and product specialists, are dedicated to the support of our clients and leverage the capabilities of our global firm to deliver to our clients. We provide an integrated approach to client servicing in order to meet the client’s full range of investment and servicing needs. Each new client is assigned to a Client Service team which consists of a Client Advisor, Marketer, Client Account Manager, Portfolio Manager and Investment Specialist.
As an Associate in Asset Management: Client Data Science within our Business Intelligence and Advanced Analytics team, you will spend each day defining, refining, and delivering set goals for our firm
Job responsibilities
- Partnering with business stakeholders to identify opportunities for leveraging advanced analytics. Leverage the power of AI/ML to solve complex business problems
- Embed analytics process in organizational decision making: descriptive, diagnostic and predictive and prescriptive analytics to derive better business outcomes
- Building analytical frameworks for marketing measurement – A/B testing, campaign ROI(return on investment) , cost of acquisition modeling, lifetime value, etc.
- Explore and mine data to develop a deep understanding of client behavior, segmentation and engagement models, market opportunity sizing and wallet share evaluations, build recommendation engines and personalization frameworks, build predictive call to action solutions, measurement analytics
- Contributing to and enhancing data models and feature stores. Leveraging machine learning models and techniques to target opportunities and optimize processes
- Developing tools and solutions to measure model performance over time and fostering a data-driven, innovative culture
- Acting as a proxy product-owner and consultant to provide optimal data solutions for various business problem statements / pain-points and goals
Required qualifications, capabilities, and skills
- MBA or advanced degree in Statistics, Math, Engineering or other quantitative-focused field
- Experience in an analytics role, financial services/marketing.
- Experience using computer languages (Python, Pyspark, Google Analytics, etc.) to manipulate and analyze large datasets. Story-telling acumen using Tableau, power-point etc. tools
- Sound knowledge of SQL to collate data from various sources
- Experience using machine learning libraries in Python (Numpy, Pandas, Sci-kit learn, tensorflow, .)
- Knowledge 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.)
- Strong problem-solving skills and excellent communicator (written and verbal) with strong interpersonal skills
Preferred qualifications, capabilities, and skills
- Understanding of Asset Management Business. A passion for technology, financial services and Asset / Wealth management
- A balanced approach combining judgment, analytical rigor, curiosity, open-mindedness and creativity. Excellent communication skills with a knack of converting data into stories
- Ability to multi-task and understand priorities/workflows. Self-motivated, team player with strong work ethic
- Ability to build relationships across global teams
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