Job Description
The Data Scientist II - FI Solutions plays a crucial role in delivering our solutions today and will play a more prominent role in our future. A typical data science project has a solid mathematical foundation, an exploratory dimension, and a data-driven workflow. At Vericast, our data science projects have strong foundations on machine learning, data engineering, and modeling. We are building a privacy-centric future of digital advertising by focusing on web content. We are connecting web content to consumer interest and action, ultimately driving which ads are shown on a webpage.
The Data Scientist II - FI Solutions, is passionate about using cutting edge technology and data science methods to solve unique and complex problems within the Financial Services industry. The Data Scientist II - FI Solutions is innately curious about how data can be used to tell a story and inform decisions. The Data Scientist II - FI Solutions is an integral part of a cross-disciplinary team working on highly visible projects that improve performance and grow the intelligence in our Financial Services marketing product suite. Our day-to-day work is performed in a progressive, high-tech workspace where we focus on a friendly, collaborative, and fulfilling environment.
KEY DUTIES / RESPONSIBILITIES
- Leverage a richly populated feature stores to understand consumer and market behavior. 20%
- Implement a predictive model to determine whether a person or household is likely to open a lending or deposit account based on the advertising signals they've received. 20%
- Derive a set of new features that will help better understand the interplay between geography and audience features to improve model performance. 20%
- Work collaboratively with Data Engineering and Analytics teams to develop new products with applied AI and bring them to market. 20%
- Participate in planning, roadmap, and architecture discussions to help evolve our AI processes to improve revenue-generating products. 20%
Qualifications
EDUCATION
Bachelor’s Degree (Required)Master's Degree in a quantitative discipline (Computer Science, Mathematics, Engineering, Statistics) (Required)Doctorate Degree (Preferred)EXPERIENCE
5-10 years of experience within the Data Science space.In lieu of the stated education and experience requirements, a combination of experience and education will be considered.Experience with web or digital analytics tools ( Adobe Analytics, Google Analytics, WebTrends) preferred.KNOWLEDGE / SKILLS / ABILITIES
Conduct in-depth user journey analysis to pinpoint engagement gaps, conversion barriers, and high-performing paths.Identify opportunities in print, SEO, paid ads, and digital marketing optimization by using data from POS systems, Google Analytics and media delivery platforms.Understanding and experience with Machine Learning workflows and model productionalization.Expertise in analysis or design of experiments for standard and adhoc analysis, interpreting results to drive marketing strategies.Familiarity with Spark Framework within an On-Premise Big Data Environment.Good analytical skills, with expertise in analytical toolkits such as Regression, Tree-based Models, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modeling, and predictive analysis.Proficient in Python / PySpark collaborative development in an industry setting.Ability to create Data-Driven presentations and reports for technical and non-technical stakeholders.Proven track record of leveraging data to optimize marketing campaigns and improve customer engagement.OTHER
Serve as a mentor to junior and less experienced data scientists by providing guidance, sharing technical expertise, and supporting their professional development through regular feedback, code reviews, and collaborative problem-solving.