Sr. Data Scientist - Customer Lifetime Value Modeling

We have an immediate need for a Senior Data Scientist with Customer Lifetime value modeling and can function without the aid of a BI team to get their data.  This position is located in New York (Hybrid or Remote). This is a full-time / direct hire opportunity with a competitive salary and bonus plan. You must be a US Citizen or Green Card holder to be considered. No sponsorship or visa transfers are available for this role.

What You’ll Do

• Lead initiatives to develop new products and solutions that provide advanced consumer insights and predictive analytics for brands.
• Focus on product development for partnerships, enhancing the capability of brands to understand and engage with their consumers effectively.
• Utilize data mining and statistical analysis to generate insights from consumer profiles, contributing to the Company's innovative consumer insights platform.
• Leverage third-party data sources, including Shopify, to enhance the breadth and depth of our consumer insights.
• Collaborate with sales and product teams to identify opportunities for growth and innovation in the consumer insights domain.
• Engage in high-stakes presentations, requiring strong presentation skills to convey complex data in a clear and impactful manner.

What You Need

• ETL experience or SQL (needs to be able to move data)
• Customer Lifetime Value Modeling
• Minimum 4 years as a Data Scientist, with at least 8 years of work experience in analytics or consumer insights.
• Demonstrated expertise in manipulating large data sets and building statistical models, with a focus on consumer insights.
• Proficiency in Python, SQL, and experience with third-party data sources like Shopify.
• Strong background in statistical analysis and problem-solving, with a specific focus on product development and consumer behavior insights.
• Excellent written and verbal communication skills, particularly in presentation contexts.
• An entrepreneurial, self-motivated, detail-oriented, and organized approach to work.
• Bachelor's or higher degree in Computer Science, Engineering, Economics, Mathematics, Statistics, Data Science, or a relevant quantitative field.