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.
