We are HR Data and Analytics, a centralized global team responsible for all aspects of workforce data strategy, analytics and data governance. We have a vision to help make individuals, teams, and businesses at JPMC among the most engaged and productive in the world. Our mission is to create workforce insights that allow leaders to make evidence-based people decisions that help drive measurable business outcomes.

As a Data Science Lead in our HR Data & Analytics team, you are not only strong in both quantitative skills and business acumen, but also a great collaborator with your team members and internal clients. You translate abstract business asks to analysis tasks or agenda, conduct analysis, and communicate results with relevant parties. You are a valuable contributor to our intellectual capital – Accumulate institutional knowledge about our workforce, explore and develop different tools and analysis methods in the context of HR, and create relevant templates to drive synergy across HR analytics work. Last but not least, you embrace a mentoring mentality in developing junior team members through collaboration in analysis work.

Job Responsibilities

Conduct analysis based on past and current HR and business data to generate relevant, actionable insights that answer the question of “so-what,” and support leadership in making evidence-based decisions. In support of this analysis, design and implement relevant analytics, explanatory models, and, if appropriate, predictive models,  including exploratory data analysis, feature engineering, , data quality checks, and model performance evaluation. Manage the design, build, and delivery of analytical solutions with a pragmatic approach in evaluating multiple solutions. Develop new analysis ideas based on observations in the existing book of work and data assets. Work with business users to measure the realized benefit of delivered solutions. Capture and understand end-user requirements, translate them into customized analytical solutions, and communicate results via reports, presentations, and insightful visualizations. Collaborate with team members to deliver analysis results to business leaders. Collaborate with data sourcing and technology teams for data acquisition, platform onboarding and enhancement, and production deployment. Adhere to relevant regulatory, compliance, and control policies and procedure. Follow best practices when handling proprietary and sensitive data.

Required Qualifications, Capabilities, and Skills

7+ years of experience with a Bachelor's degree in a related social science, business, or quantitative analysis discipline (e.g., Economics, Business, IO Psychology, Statistics, Business Analytics, Computer Science), or 3+ years with a higher degree, and experience in industry or at a top management consulting firm. Experience in Human Resources for Financial Services, or allied areas, including people analytics, labor market research, finance, economics, consumer/user behavior, or the financial services industry Proficiency in quantitative analysis and statistical data modeling, and associated software (e.g., Python and its associated open source libraries, R, SPSS),  to implement classical statistical techniques such as hypothesis testing, multiple regression, multivariate analysis, for regression analysis, as well as supervised and unsupervised algorithms for machine learning, and model performance evaluation. Experience with data wrangling tools (e.g., SQL, Alteryx) and working with large datasets (millions of records) for data exploration and analysis. Familiarity with modern techniques for natural language processing, including the use of contextualized embeddings and pretrained language models, including LLMs, for text classification, summarization, and named entity recognition Proficiency with reporting and visualization tools (e.g., Tableau, PowerBI) and advanced Excel skills (e.g., pivot tables,  Analysis ToolPak). Ability to articulate data insights in a business context through customized reports, visualizations, and presentations, and discuss complex issues in easy-to-understand ways. Experience in consulting, client engagement, or technical project execution with a focus on data and analytics solution delivery.

Preferred Qualifications, Capabilities, and Skills

Experience with project planning and execution, such as agile practices, dependency planning, and tools like JIRA; pragmatic problem solving across multiple types of issues in project work. Experience managing ambiguity and stakeholder relationships across multiple business functions. Experience with cloud services and data analytics frameworks (e.g., AWS, SageMaker, Starburst/Trino, Databricks/Spark).