Job Responsibilities:
- Perform big-data analysis and improve LLM model results for conversational insights in both AWS and on-premises environments.
- Transform data, reporting, and business driver analysis to improve existing operational processes and applications. Identify customer interactions and events across various channels that cause customer and specialist frictions.
- Partner with cross-functional teams to consolidate business assumptions with productionized data to validate hypotheses and identify production flaws.
- Create and present concise insights to peers, the executive leadership team, and business partners.
- Proactively investigate issues and problems in data collection, model building, and production phases.
- Document SQL/Python codebase, data dictionary, and model outputs in a clear and concise way.
- Work as a member of agile, digital, tribes, or scrum teams to provide data and analytics support for new product development.
Required qualifications, capabilities and skills:
- Solid programming skills in SQL.
- Experience in big data ETL for structured/unstructured database
- Experience in Machine Learning, NLP, and LLM.
- Strong writing and presenting skills.
- Detail oriented problem-solver with a knack for meeting tight deadlines.
- Hands-on team player with full of curiosity to operate in a self-directed manner.
- Work experience with Excel PivotTable, presentation PPT and data wrangling & visualization tools including Tableau, Alteryx, SQL, and Jupyter Notebook.
- Trained in multivariate statistics, regressions, SQL, Spark, data analytics & visualization.
- Work experience in AWS, Spark/EMR, ChatGPT, Confluence and Snowflake.
Preferred qualifications, capabilities and skills:
- Extensive experience in consumer banking units such as operations, servicing, collections, or marketing.
- Solid understanding in multi-linear regression, logistic regression, clustering, classification techniques, controlled experiments, and causal inference methods (DD/PM/NN).
- Communication - Ideal candidate would be able to develop and deliver concise presentations that clearly articulate challenges, actions, and results for complex matters - creating clarity and a bias for action with key stakeholders. Candidate should be able to crisply synthesize data into actionable insights for executive leadership.
- Good understanding of IT processes and databases. Being able to work directly with data owners/custodians and contributing to building analytics data hub.
- Flexibility/adaptability, ability to listen and defending or changing direction based upon team and stakeholder consensus.
- Bachelor’s degree in Economics, Data Analytics, Statistics, or a STEM related field AND 3 years of work experience in Analytics, preferably with financial services firms and/or in operations/contact center functions