Job Description

About Us:  

Cookie Finance is a venture-backed, rapidly growing technology-driven accounting startup that works exclusively with content creators and social media influencers, one of the fastest-growing industries in the world. We work with clients across YouTube, Instagram, TikTok and other social platforms. Our Cookie Jar software platform is used by our customers and employees to make finances for creators simple and empowering. 

Position Overview:  

We are looking for a talented data scientist to join our growing engineering team. We are developing a product within our Cookie Jar platform that combines financial data with social analytics to help our customers make better business decisions.

You will be the lead data scientist on this project so we are looking for someone that can think strategically and actively influence product development while applying statistical and ML/AI techniques to build something powerful and unique. 

This is a hybrid position with expectations to work in our office 3 days a week and 2 days from home. We have offices in Syracuse, NY and Richmond, VA, although most of the engineering team is based in Syracuse. You will report directly to the CTO. 

Key Responsibilities:

• Analyze large datasets to identify trends, opportunities, and actionable insights
• Build predictive models and algorithms to help our customers grow their businesses
• Collaborate with an engineering team of full stack (Node/React) developers, designers, and a data engineer
• Develop clear, compelling data visualizations
• Stay up-to-date with emerging technologies and industry trends to continually improve development processes

Required Qualifications:

• 3+ years of professional experience as a Data Scientist
• Proficiency in Python and data science libraries (e.g., Pandas, NumPy)
• Solid experience with SQL and relational databases (e.g., PostgreSQL)
• Proven ability to build and validate predictive models
• Excellent communication skills, particularly in explaining complex data insights.

Preferred Qualifications:

• B.S. in Data Science, Computer Science, Statistics, Mathematics, or a related field
• Experience with data visualization tools (e.g. Tableau, Power BI)
• Familiarity with AWS Sagemaker or other cloud platforms
• Knowledge of machine learning frameworks (e.g. TensorFlow, PyTorch)
• A good sense of humor

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