Head of Generative AI Innovation | Data Scientist

** Candidate must have worked in the Financial Industry
** The company operates on EST (Eastern Time Zone) including all morning scrums
** Having worked on pricing engines is a bonus
**Onsite Reporting
**Onboarding January 2025


We are:
A well-funded and highly experienced FinTech startup composed of Wall Street and Silicon Valley veterans. Utilizing decades of experience from trading floors and global financial markets to the leading edge of artificial intelligence, we have created a new type of trading platform that opens investment opportunities to all investors, not just accredited.


You are:
A highly skilled and experienced Data Science Leader, you love to push beyond traditional boundaries to innovate and create unprecedented solutions. You are proficient in building predictive pricing models and developing algorithms that forecast prices based on historical data and market trends. With expertise in analyzing various types of data, you excel at identifying patterns that others might overlook. The ideal candidate is creative in their approach to problem-solving and focuses on the high-value impact of their work. You thrive in a fast-paced environment, think outside the box, and can adapt to evolving requirements.


The Job:
As the Director of Data Science, you will lead dedicated teams tasked with the development of predictive models for precise asset valuation. These teams range from data extraction, data analysis for normalization and cleaning, data pipelines and storage, research, production quality models. Your impressive teams have close to 100 issued patents working in production for companies around the world. This team is very hands-on and you will be directly involved in actually building and deploying your work into production. This position calls for a high degree of professionalism, technical expertise, and a commitment to delivering innovative and sustainable solutions.


Responsibilities
Lead, mentor, and manage a team of data scientists, analysts, and engineers
Design, develop and refine pricing models to forecast market-prices for assets based on various types of data
Implement anomaly detection systems to identify and react to unexpected market conditions
Conduct complex statistical analyses to understand trends and patterns in large datasets
Collaborate with the data engineering team to deploy your models, ensuring accuracy, efficiency, and scalability
Validate and enhance model accuracy and robustness
Explain model behaviors and outcomes to stakeholders in a clear, accessible manner


Required skills and qualifications
TEAM PLAYER and PROVEN LEADER
Master’s degree or PhD in Data Science, Statistics, Computer Science, Economics, or a related field with at least 6 years of relevant experience in market-pricing
Demonstrated experience in hiring, retaining, and scaling geographically dispersed, high-performing teams.
Significant experience influencing product strategy and driving change across organizational boundaries through clear and compelling communication of data-driven insights and analyses
Proficient in Python, R, Scala, or similar programming languages
Have worked and excelled in both startup and institutional environments
Direct experience with dynamic pricing or revenue management in key industries such as real estate, energy, travel, automotive or financial services
Excellent communication and collaboration skills
Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, Pandas, Prophet).
Strong analytical skills, attention to detail, and the ability to work effectively in a team environment
Excellent problem-solving abilities and a commitment to delivering high-quality software solutions
Familiarity with deploying machine learning solutions on cloud platforms like AWS, Azure, or Google Cloud
Resourceful, with a strong ability to develop solutions, build relationships, and see opportunities that others might miss
Published work in reputable Machine Learning and Data Science forums
Industry