Data Scientist - FI Solutions

Vericast is a big data company. We receive on average over 100 billion intent signals daily, which assist in generating a deep understanding of a person's interest and in-market signals across 1,300 interest topics. This is coupled with strong geographic targeting, as over 30 billion location signals are collected daily from over one million retail stores and over 120 million households.

Data Science 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. This is also true 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.

To continue our journey, we are seeking data science experts who are passionate about using cutting edge technology and conceiving innovative methods to solve unique and complex problems. As a Data Scientist - FI Solutions at Vericast, your contributions will help us stay at the forefront of the AdTech industry.

We are seeking a Data Scientist-FI Solutions who is passionate about using cutting edge technology and data science methods to solve unique and complex problems within the Financial Services industry. The ideal candidate is innately curious about how data can be used to tell a story and inform decisions. You have honed your skills through a combination of education, work experience, and hobbies. You are excited about the complexity and challenges of creating intelligent, high-performance systems while working with a highly experienced and driven data science team.

If this described you, we are interested. You can be 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%

Requirements

EDUCATION

• Bachelor's of Science (BS) degree in quantitative discipline (Computer Science, Mathematics, Engineering, Statistics) (Required).
• Master's pf Science (MS) degree in relative field (Computer Science, Mathematics, Statistics) (Preferred).

EXPERIENCE

• 3-5 years of experience within the Data Science space.

KNOWLEDGE/SKILLS/ABILITIES

• Ability to churn through and gain insights from high volumes of data using distributed processing.
• Ability to create Data-Driven presentations and reports for technical and non-technical stakeholders.
• 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, predictive analysis.
• Proficient in Python/PySpark collaborative development in an industry setting.
• Proven track record of leveraging data to optimize marketing campaigns and improve customer engagement.
• Understanding and experience with Machine Learning workflows and model productionalization.