Overview

Be among the first 25 applicants. Baselayer is built by financial institutions, for financial institutions, with experience across banks, Fortune 500 tech companies, fintech unicorns, and AI experts. Started in 2023 by Jonathan Awad and Timothy Hyde, Baselayer has raised $20 million and reached $2 million ARR, serving more than 2,000 financial institutions and government agencies. Baselayer is at the forefront of fraud prevention and regulatory compliance.

About you

You want to learn from the best, get hands-on experience, and work to reach your full potential. You aim to be an impeccable data scientist working with cutting-edge AI/ML technologies.

• You have 1-3 years of experience in data science, with Python and data-driven modeling
• You are comfortable working with large-scale datasets and extracting meaningful insights
• You have a strong foundation in statistics and machine learning, with interest in applying advanced techniques to real-world problems
• You prioritize data integrity and ethics, especially with sensitive information in regulated environments like KYC/KYB
• You have a detail-oriented mindset and create clear, interpretable analyses that drive actionable insights
• You thrive in a high-trust, ownership-focused environment and can translate between technical concepts and business objectives
• You are a problem-solver who navigates ambiguous data challenges
• You are a proactive self-starter who thrives in dynamic settings
• You are highly intelligent and analytical, taking pride in data-driven solutions
• You are highly receptive to feedback and committed to continuous improvement

Responsibilities

• Data Analysis & Insight Generation: Analyze 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 KYC/KYB workflows
• Data Pipeline Development: Collaborate with engineering to design and implement data pipelines transforming raw data into useful features
• AI/ML Application: Apply advanced techniques, including LLMs, to solve business problems in identity verification
• Experiment Design & Evaluation: Design experiments to validate hypotheses, measure impact, and improve data science solutions
• Data Visualization & Communication: Create visualizations and presentations that communicate findings to technical and non-technical stakeholders
• Feature Engineering: Develop features from raw data to enhance model performance
• Performance Monitoring: Establish metrics and monitoring to track effectiveness and identify improvement opportunities
• Research & Innovation: Stay current with data science and ML research and evaluate potential approaches
• Hybrid in SF. In office 3 days/week
• Flexible PTO
• Smart, genuine, ambitious team

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

Seniority and Employment

• Seniority level: Entry level
• Employment type: Full-time
• Job function: Engineering and Information Technology
• Industries: Technology, Information and Internet