About Figure
Figure Technology Solutions, Inc. (Nasdaq: FIGR; OPEN: FGRS) is the leading blockchain-native capital marketplace for the origination, funding, sale and trading of tokenized assets. More than 480 partners use its loan origination system and capital marketplace. Collectively, Figure and its partners have originated over $30 billion of loans to date, among other products. The fastest growing components are Figure Connect, its credit marketplace, and Democratized Prime, Figure’s on-chain lend-borrow marketplace. Figure’s ecosystem also includes DART (Digital Asset Registry Technology) for asset custody and lien perfection, and $YLDS, a yield-bearing stablecoin registered with the SEC as a security under the Securities Act of 1933.
Figure is the market leader in real-world asset (RWA) tokenization. The company has received triple-A ratings ratings from S&P and Moody’s on multiple loan securitizations, the first of its kind for blockchain finance.
We’re proud to be recognized as one of Forbes’ Top 50 Fintech Companies and CNBC’s World’s Top Fintech Companies.
About the Role
We’re looking for a Senior Data Scientist to join our growing team! As Senior Data Scientist, you’ll develop and apply modern machine learning and artificial intelligence across a range of products and business problems. You’ll combine strong computer science foundations, rigorous experimental judgment, and the ability to turn advances in AI into reliable systems with measurable business impact. The work spans document intelligence, multimodal systems that combine text, images, and structured data, and the adaptation of foundation models using proprietary datasets. These models support complex workflows in regulated financial services, where accuracy, explainability, data governance, reproducibility, and careful evaluation are essential. You’ll work across the full machine learning lifecycle and turn successful approaches into reusable AI capabilities, patterns, and components that support multiple teams rather than building a one-off solution for every problem.
What You’ll Do
- Identify high-impact opportunities for machine learning and AI in partnership with product, engineering, operations, and business teams
- Design, train, fine-tune, and evaluate machine learning and deep-learning models
- Work with foundation models across language, vision, and multimodal applications
- Develop robust datasets, features, training pipelines, and evaluation frameworks
- Run efficient experiments on GPU infrastructure and improve model quality, speed, and cost
- Compare alternative modeling approaches and make clear recommendations based on empirical results and business impact
- Build reusable modeling components, evaluation frameworks, and implementation patterns that accelerate work across teams and projects
- Establish clear interfaces and standards that allow other teams to adopt proven AI capabilities without rebuilding the underlying modeling work
- Build models and supporting systems that are reproducible, testable, and suitable for production use
- Partner with ML and software engineers on deployment, monitoring, reliability, and ongoing model improvement
- Communicate results, limitations, and tradeoffs clearly to both technical and non-technical stakeholders
- Stay current with advances in machine learning and determine when emerging techniques are mature enough to create practical value
- Turn ambiguous business needs into well-defined machine learning problems and measurable success criteria
- Build models that improve real customer or operational outcomes, not only offline metrics
- Make thoughtful tradeoffs among model quality, complexity, latency, reliability, and cost
- Create reusable foundations that allow multiple teams to apply proven AI capabilities to new problems more quickly and consistently
- Help raise the organization’s technical standards for experimentation, evaluation, and production AI
What We Look For
- Bachelor’s or advanced degree in Computer Science, Machine Learning, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent practical experience
- 5+ years of experience developing machine learning solutions, including experience taking models beyond initial experimentation
- Strong programming and software-engineering skills, particularly in Python
- Strong foundations in machine learning, statistics, algorithms, data structures, and experimental design
- Hands-on experience with deep-learning frameworks such as PyTorch or TensorFlow
- Experience training or fine-tuning transformer-based, vision, or multimodal models
- Experience working with GPUs and understanding the practical constraints of model training and inference
- Ability to work with large, complex, and imperfect datasets
- Demonstrated ability to own open-ended problems from initial investigation through implementation and measurement
- Demonstrated ability to generalize successful solutions into reusable capabilities rather than one-off models
- Strong communication and cross-functional collaboration skills
- Master’s degree or PhD in Computer Science, Machine Learning, or a related field (preferred)
- Experience with distributed training, model optimization, quantization, or parameter-efficient fine-tuning (preferred)
- Experience deploying and monitoring machine learning models in production (preferred)
- Familiarity with cloud infrastructure, distributed data processing, and modern ML development platforms (preferred)
- Experience building AI systems in regulated, risk-sensitive, or high-stakes environments (preferred)
- Contributions to applied research, open-source projects, patents, or production AI products (preferred)
- Adhere to all company security policies and data handling procedures.
- Complete mandatory security awareness training within required timeframes.
- Promptly report any suspected security incidents or suspicious activity to the Security team.
Salary
- Base Compensation Range: $132,000 - $198,000/yr
- 25% annual bonus target, paid quarterly
- Company equity in the form of RSUs
This is the compensation range for the role in the United States. Actual compensation may vary based on a candidate’s experience, skills, location, internal equity, and evolving business needs. While most offers are generally made within the middle of the range, final compensation is determined based on the factors above.
Benefits
- Comprehensive medical, dental, and vision coverage, with 100% employer-paid premiums for employees and their dependents on select plans
Company HSA, FSA, Dependent Care FSA, 401(k), and commuter benefits
Employer-paid life and disability insurance
11 observed holidays and PTO plan
Up to 12 weeks of paid family leave
Continuing education reimbursement
Depending on your residential location certain laws might regulate the way Figure manages applicant data. California Residents, please review our California Employee and General Workforce Privacy Notice for further information. By submitting your application, you are agreeing and acknowledging that you have read and understand the above notice.
Figure will not sponsor work visas for this position. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.
#LI-SB1 #LI-Hybrid
Skills Required
- Bachelor's degree or advanced degree in Computer Science, Machine Learning, Electrical Engineering, Applied Mathematics, or a related technical field, or equivalent practical experience
- 5+ years of experience developing machine learning solutions, including taking models beyond initial experimentation
- Strong programming and software-engineering skills, particularly in Python
- Strong foundations in machine learning, statistics, algorithms, data structures, and experimental design
- Hands-on experience with deep-learning frameworks such as PyTorch or TensorFlow
- Experience training or fine-tuning transformer-based, vision, or multimodal models
- Experience working with GPUs and understanding practical constraints of model training and inference
- Ability to work with large, complex, and imperfect datasets
- Ability to own open-ended problems from initial investigation through implementation and measurement
- Ability to generalize successful solutions into reusable capabilities rather than one-off models
- Strong communication and cross-functional collaboration skills
- Master's degree or PhD in Computer Science, Machine Learning, or a related field
- Experience with distributed training, model optimization, quantization, or parameter-efficient fine-tuning
- Experience deploying and monitoring machine learning models in production
- Familiarity with cloud infrastructure, distributed data processing, and modern ML development platforms
- Experience building AI systems in regulated, risk-sensitive, or high-stakes environments
- Contributions to applied research, open-source projects, patents, or production AI products
Figure Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Figure and has not been reviewed or approved by Figure.
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Healthcare Strength — Health coverage is fully employer‑paid on select plans for employees and dependents, alongside company‑paid life and disability insurance and mental‑health support. This breadth and low out‑of‑pocket cost are highlighted as standout aspects of the package.
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Leave & Time Off Breadth — Time off is positioned as flexible with generous PTO, paid holidays, and sick time. Paid family leave is available for both birthing and non‑birthing parents.
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Equity Value & Accessibility — Equity is broadly offered with renewal grants and the option to take performance bonuses as equity. This structure signals accessible ownership across roles.
Figure Insights
What We Do
Figure has applied blockchain technology across a series of real-world applications that are delivering real and immediate value to everyday consumers across sectors, including loan origination, private company cap table and fund management, security markets and payments. Figure has and continues to develop innovative products and services that seek to bypass traditional incumbents within the financial services industry. Simply put, Figure is delivering on the promise of blockchain technology. Over $15B in transactions have been conducted on the Provenance Blockchain, a layer 1 designed for financial services, built and deployed by Figure. As one of the first lenders to fully use blockchain technology, Figure is driving adoption across the lending ecosystem and providing stakeholders the benefit of an immutable record of asset ownership on the Provenance Blockchain. Figure’s HELOC product has enabled over 85,000 households across 45 states to unlock a combined $6 billion in equity from their homes. These lines of credit give people the opportunity to fund home improvement projects, secondary education, and more. Figure is a regulatory powerhouse, boasting over 200 lending, servicing and money transmission licenses, SEC approval as an Alternative Trading System, and FINRA approved broker-dealer status. While some fintech companies aim to compete with traditional banks, Figure has stuck to expanding use cases for blockchain in finance and creating tech-enabled solutions for deep financial change in the markets. The company's iterative approach to product development has helped it to meet the evolving needs of its customers.
Why Work With Us
Figure creates tech-enabled, cutting-edge solutions for deep financial change, meeting the evolving needs of its customers. As the only firm leveraging blockchain technology to create real-world applications and immediate value to everyday consumers, Figure is effectively bridging the gap between the digital asset and traditional finance spaces.
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