In ISDA at JPMorgan Chase, our role involves solving challenging business problems through data science and machine learning techniques across all of Corporate technology and the supported Corporate Functions. corporate functions, including Compliance, Finance, CAO, Audit and Legal.

As a Data Scientist- Vice President, you will help build robust and scalable solutions for various banking domains, and also enable the services to be deployed and integrated into existing business workflow. This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the business processes of a leading global bank.

Job Responsibilities: 

• Builds relationships with internal teams and clients and is passionate about unlocking value using AI and Machine learning
• Demonstrates intellectual curiosity for solving difficult problems
• Is a self-starter with technical knowledge and a hands on approach to using our data assets both efficiently and effectively
• Develop approaches for understanding each individual client and their behavior to deliver highly impactful ML models
• Develop, plan and execute analytical projects as an individual contributor and in teams. 
• Lead the “productionzation” analytical insights and machine learning models in collaboration with product managers, end users, developers, and other stakeholders to integrate data discoveries and processes into operational capabilities

Required Qualifications, Capabilities and skills :

• Advanced degree in an analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis, Operations Research).
• Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets.
• Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop.
• Experience in analyzing complex problems and translating it into an analytical approach.
• Experience in Supervised and Unsupervised Machine Learning including Classification, Forecasting, Anomaly Detection, Pattern Detection, Text Mining, using variety of techniques such as Decision trees, Time Series Analysis, Bagging and Boosting algorithms, Neural Networks, Deep Learning.
• Strong software engineering experience
• Experience with analytical programming languages, tools and libraries (Python ecosystem preferred, but R will be considered).
• Experience in SQL and relational databases, Big Data technologies e.g. Spark/Hadoop and Cloud technologies.
• Strong leadership, stakeholder management, communication, partnership and teamwork skills.
• Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision.