Senior Data Quant - #19543356
Bank of America Corporation
The Enterprise Process Oversight (EPO) Reporting and Analytics team leverages engineering, analytics, and NLP / machine learning to organize customer feedback to drive change across an amazing and vibrant company. Meaningful impact can be made since the EPO engages with the largest organizations within Bank of America.
The job requires a deep understanding of statistical methods and their practical applications, managing our existing and growing model inventory, both quant models and AI / NLP models. Provide succinct documentations to senior leaders as well as support model risk management.
- Proficiency in statistical analysis using either Python or R
- Model customer behavior through quantitative models including Logistic Regression, Survival Analysis, Decision Trees, and time series methods in Python
- Experience producing detailed, technical white paper for model documentation and testing
- Create end-to-end analysis (data or statistical) from data extraction to end-state manifestations, whether in a business intelligence solution or PowerPoint presentation
- Test, evaluate, and maintain robust data analysis and reporting for management to make timely, informed decisions
- Identify relationships and trends in data, as well as any factors that could affect the results of research.
- Question and validate assumptions. Escalate identified risks and sensitive areas in terms of methodology and processes
- Support data processes: provide the team with ad-hoc analysis, automated dashboards, and self-service reporting tools so that everyone gets a good sense of the state of the business
- Develop executive level presentations; turn data, analytics and insights into compelling visual effects that can be easily understood by business partners (PowerPoint/ Tableau)
- Generate new ideas, concepts and models to improve methods of obtaining and evaluating quantitative and qualitative data
- Prioritize and execute in the face of ambiguity: distill ambiguous problems, adapt your tools to answer complicated questions, and identify the trade-offs between speed and quality of different approaches
- Maintain a customer-centric focus: strive to be a domain and product expert through data, develop trust among your peers and stakeholders, and ensure that your team has access to data to make decisions
- Master's degree or minimum 4-6 years of equivalent professional experience in a statistics-heavy discipline (engineering, mathematics, operations research etc.)
- As this position requires extensive documentation around highly technical white papers, having a strong fundamental understanding of statistics approaches is a must
- Experience pulling data from SQL-based relational DB as well as working with unstructured big data systems (Hadoop/Hive/MapReduce)
- Hands on experience pre-processing unstructured text using Natural Language Processing techniques in Python or Spark
- Have built and applied word embedding workflows
- Ability to indirectly manage peer level associates who are part of problem solving teams
- Building, validating, and running machine learning models, including natural language processing models
- Deep statistical skills utilized in hypothesis testing, quasi experimentation, and developing sampling strategies
- Ability to present technical issues to nontechnical audiences and to clearly articulate findings in verbal and written form.
- Working knowledge of Tableau; certification a plus
1st shift (United States of America)
Hours Per Week:
Learn more about this role