Overview
Skills
Job Details
NO C2C
Bank
Columbus OH- work onsite 4 days a week
Needed ASAP
Contract to Hire
Work on W2
NO C2C
Data Scientist
The skills that will be critical will be Python or R and a firm understanding of SQL along with foundationally understanding what data is needed to perform studies now and in the future. For a high-level summary that should help describe what this person will be asked to do alongside their peers:
Feature & Functional Design
Data scientists are embedded in the team s designing the feature. Their main job here is to define the data tracking needed to evaluate the business case things like event logging, Adobe tagging, third-party data ingestion, and any other tracking requirements. They are also meant to consult and outline if/when business should be bringing data into the bank and will help connect business with CDAO and IT warehousing and data engineering partners should new data need to be brought forward.
Feature Engineering & Development
The same data scientists stay involved as the feature moves into execution. They support all necessary functions (Amigo, QA, etc.) to ensure data tracking is in place when the feature goes live. They also begin preparing to support launch evaluation and measurement against experimentation design or business case success criteria.
Feature Rollout & Performance Evaluation
Owns tracking the rollout, running A/B tests, and conducting impact analysis for all features that they have been involved in the Feature & Functional Design and Feature Engineering & Development stages. They provide an unbiased view of how the feature performs against the original business case along with making objective recommendations that will provide direction for business. They will roll off once the feature has matured through business case/experiment design and evaluation.
In addition to supporting feature rollouts
Data scientists on the team are also encouraged to pursue self-driven initiatives during periods when they are not actively supporting other projects. These initiatives may include designing experiments, conducting exploratory analyses, developing predictive models, or identifying new opportunities for impact.
Will balance analysis with development.