Staff Data Scientist, Methodologies

🔥 6 minutes ago

🇺🇸 United States – Remote

💵 $192k - $240k / year

⏰ Full Time

🔴 Lead

📊 Data Scientist

👻 Ghost score 1%

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Tilt (formerly Empower)

WebsiteLinkedInAll Job Openings

201 - 500 employees

💳 Fintech

👥 B2C

💸 Finance

Fintech • B2C • Finance

Tilt is a financial technology company that provides cash advance, lines of credit, and credit card services aimed at empowering customers financially. With an emphasis on accessibility, Tilt offers flexible repayment plans and eligibility irrespective of a customer's credit history, enabling individuals to qualify based on their real-time financial habits. The platform is user-friendly, boasting positive customer experiences and a high rating, making it a convenient option for those seeking to manage their finances and build credit effectively.

📋 Description

• Develop and test modeling approaches using deep learning architectures such as transformers, embeddings, and neural networks • Build and refine frameworks integrating with existing ML pipelines for credit modeling and loss prediction • Collaborate with data scientists, engineers, and product partners to translate complex ideas into practical solutions • Experiment with pretraining and fine-tuning representation learning techniques on financial data • Share findings and mentor others to grow deep learning capability • Measure model impact through customer and partner outcomes, not only accuracy • Use agentic development tools such as Claude Code and Codex for experimentation, feature engineering, and model iteration • Design and ship specialized agents supporting data science and business workflows • Help advance foundational modeling approaches across Tilt’s products and improve access to fairer credit

🎯 Requirements

• Experience with deep learning, including neural networks, embeddings, or transformers • Comfort working with modern ML frameworks such as PyTorch or TensorFlow • Experience applying machine learning to real-world problems, ideally in financial services • Strength connecting data science to measurable business outcomes • Clear, thoughtful communication of technical ideas • Bonus: hands-on experience building with LLMs or agent frameworks, or excitement to learn • Willingness to learn, experiment, and collaborate

🏖️ Benefits

• WFH office reimbursement • Competitive compensation packages • Generous equity • Flexible health plans at every premium level • Substantial health-plan subsidies • Direct exposure to the leadership team • Paid global onsites twice yearly • Growth opportunities based on contributions rather than rigid promotion timelines