Senior Data Scientist (Gen AI)
Bluevine India · Bengaluru ·
- Work mode
- Hybrid
- Seniority
- Senior
- Category
- Data science
- Experience
- 5+ years
- Visa sponsorship
- Yes
- Company size
- 51-200
Bluevine India · Bengaluru ·
Bluevine - US · Jersey City, NJ
Bluevine - US · Jersey City, NJ
Amgen · India - Hyderabad
Sonatype · Hyderabad, India
Designs and implements generative AI solutions for financial risk modeling and fraud detection using LLMs and Python, collaborating with cross-functional teams in a hybrid office setting.
About Bluevine
Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best.
Since 2013, we’ve supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed.
We’re innovators driven by big ideas, collaboration, and real impact. Here, you’ll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what’s next?
This is a hybrid role. At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline.
Generative AI Research:
Explore and evaluate Large Language Models (LLMs) and emerging generative AI techniques to identify impactful applications in data science.
Model Fine-Tuning & Adaptation:
Design and execute experiments to fine-tune or customize foundational models using domain-specific and internal datasets.
Applied Generative AI Solutions:
Leverage generative AI to enhance traditional machine learning use cases such as risk modeling, fraud detection, and customer analytics.
Prompt Engineering & Evaluation:
Develop effective prompting strategies and build robust evaluation and benchmarking frameworks to measure model performance and reliability.
Cross-Functional Collaboration:
Partner with data scientists and cross-functional teams to integrate generative AI capabilities into existing analytics and modeling workflows.
Knowledge Sharing & Enablement:
Act as a subject matter expert, driving adoption by sharing best practices, insights, and advancements in the generative AI space.
Benefits & Perks
pwc · Singapore