Data Scientist

About Baselayer:

Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk. Baselayer’s B2B risk solutions & identity graph network leverage state & federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and lower credit losses. 

About You:

You want to learn from the best of the best, get your hands dirty, and put in the work to hit your full potential. You're not just doing it for the win—you're doing it because you have something to prove and want to be great. You are looking to be an impeccable data scientist working with cutting-edge AI/ML technologies.

• You have 1-3 years of experience in data science, working with Python and building data-driven models
• You're comfortable working with large-scale datasets and enjoy extracting meaningful insights from complex information
• You have a strong foundation in statistics and machine learning, with particular interest in applying advanced techniques to real-world problems
• You prioritize data integrity and ethical considerations, especially when working with sensitive information in regulated environments like KYC/KYB
• You have a keen eye for detail and take pride in creating clear, interpretable analyses while optimizing for actionable insights
• You thrive in a high-trust, ownership-focused environment and are comfortable translating between technical concepts and business objectives
• Problem-solver who navigates ambiguous data challenges confidently
• Proactive self-starter who thrives in dynamic settings
• Incredibly intelligent and analytical. You take pride in your data-driven solutions
• Highly feedback-oriented. We believe in radical candor and using feedback to get to the next level

Responsibilities:

• Data Analysis & Insight Generation: Conduct comprehensive analyses of large datasets to extract actionable insights that drive business decisions in the GTM and identity verification space
• Predictive Modeling: Develop statistical and machine learning models to identify patterns, predict outcomes, and optimize processes for KYC/KYB workflows
• Data Pipeline Development: Collaborate with engineering teams to design and implement efficient data pipelines that transform raw data into useful features for analysis and modeling
• AI/ML Application: Work closely with ML engineers to apply advanced techniques including LLMs to solve specific business problems within the identity verification domain
• Experiment Design & Evaluation: Design and execute experiments to validate hypotheses, measure impact of changes, and continuously improve data science solutions
• Data Visualization & Communication: Create clear, compelling visualizations and presentations that effectively communicate complex findings to technical and non-technical stakeholders
• Feature Engineering: Identify and develop innovative features from raw data sources to enhance model performance and enable new capabilities
• Performance Monitoring: Establish metrics and monitoring systems to track the effectiveness of data science solutions, identifying opportunities for refinement and optimization
• Research & Innovation: Stay current with the latest research and techniques in data science and machine learning, evaluating new approaches for potential application to business challenges

Benefits:

• Hybrid in SF. In office 3 days/week
• Flexible PTO
• Healthcare, 401K
• Smart, genuine, ambitious team

Salary Range:
$122k – $167k + Equity - 0.05% – 0.25%