JPMorgan Vice President- Data Science Lead 

United States, New Jersey, Jersey City 

48117768

As a Data Scientist Lead - VP, you will be hands-on in analyzing large-scale data to create analytical, statistical, and data science models to uncover underlying patterns and drivers to business questions in employee relations, conduct, security, compliance, customer complaints, etc. This is a highly visible technical role that will interact with multiple internal stakeholders in translating questions into analytical domain, mastering workforce data, implementing solutions, and communicating results. You will embrace a continuous learning and innovation approach in adopting latest tools and technologies.

Job Responsibilities

• Design and implement hands-on analytics and explanatory models for workforce data in support of HR and partner business functions’ evidence-based decision.
• Build data science, statistical modeling and analytics workflows, from quality checks, feature engineering, to model performance evaluation, and collaborate with technology teams in seamless production deployment. Customize commercial or open-sources analytical solutions and create new algorithms to build proprietary solutions contributing to intellectual capital of the organization.
• Manage the design, build, and delivery of analytical solutions with a pragmatic approach in evaluating multiple solutions
• Embrace attention to detail, accountability, rigor, and robustness in data analytics, statistical models, and presenting results to a broad spectrum of stakeholders
• Capture and understand end-user requirements, translate into customized analytical solutions, communicate results via reports, PowerPoint decks, and insightful visualizations. Articulate complex issues in easy-to-understand ways
• Understand data life cycles, collaborate with cross-functional teams in business & technology, and leverage capabilities to build repeatable, scalable, and automated products.
• Create and document institutional knowledge from workforce data insights, models, and share such knowledge with relevant team members and stakeholders
• Adhere to various control functions directives, data protection policies, and regulatory requirements while handling proprietary and sensitive data.

Required qualifications, capabilities and skills

• 7+ years’ experience with Bachelors in a related data discipline (e.g., Computer Science, Economics, Business, IO Psychology, Statistics, Business Analytics, or relevant quantitative fields), and/or Master’s degree with 3+ years or equivalent industry experience in a relevant domain.
• Quantitative and statistical data modeling tools (e.g., Python, R, scikit-learn etc.) to implement a variety of methods (e.g., hypotheses testing, multiple regression, multivariate analyses), exploratory (e.g., clustering, multi-dimensional scaling), anomaly detection, and AI-ML techniques (e.g., supervised / unsupervised / reinforcement learning),application of queuing theory, constrained optimization, time series analyses.
• Deep understanding of underlying mathematical concepts and application of statistical pattern recognition (e.g., PCA, correlations), algorithms (e.g., logistic regression, gradient boosting, support vector machines, K-means), model interpretation, cost functions, and performance evaluation (e.g., ROC, hyperparameter tuning)
• Demonstrated hands-on experience in text mining and NLP analytics, such as customer/employee survey analyses, unstructured data, segment analysis, pattern detection from topic modeling, etc., using variety of commercial or open source techniques
• Experience in cloud and supporting data analytics frameworks, such as various AWS data processing services, SageMaker, Starburst, Databricks, etc.
• Intermediate proficiency with reporting and visualization tools (e.g., Tableau, PowerBI) and advanced excel skills (e.g., pivot tables, VLOOKUP, Analysis ToolPak)
• Demonstrated ability to articulate data insights in business context via customized reports, visualizations, and presentations
• Versatile in learning and upskilling different software, data processing frameworks, and relevant technologies
• Relevant experience in consulting, client engagement, or technical project execution with demonstrated experience in leading data & analytics solution delivery

Preferred qualifications, capabilities and skills

• Domain knowledge or prior experience in HR, employee relations, recruitment, compensation, labor market research, customer interaction data preferably in the financial services industry
• Experience with modern techniques, such as graph databases for network analyses, Generative AI & LLMs
• Demonstrated experience in learning new areas of focus – especially corporate support functions, compliance, global security, etc., as relates to HR matters
• Experience managing ambiguity and stakeholder relationships across multiple business functions
• Experience with project management concepts, such as agile practices, dependency planning, JIRA, etc.