Data Science Lead

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, weve 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.

Were innovators driven by big ideas, collaboration, and real impact. Here, youll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape whats 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.

About the Role:

We are building a cutting-edge data science team in India and are looking for an experienced Data Scientist lead with a strong focus on marketing analytics and campaign modeling. In this role, you will apply your expertise in predictive modeling, experimental analysis, and data-driven decision-making to enhance and optimize our direct mail and paid media marketing efforts.

You will play a key role in developing response models (to predict which leads are likely to engage) and approval models (to predict product approval likelihood), improving customer targeting, and maximizing marketing ROI. This is an exciting opportunity to join a global team and help drive acquisition growth through data science innovation.

Key Responsibilities:

Marketing Model Development & Optimization

• Design and build response models to predict the likelihood of customer engagement with campaigns.
• Develop approval models to estimate a leads probability of being approved for financial products.
• Analyze match backs (expected value calculations) to support decisions for direct mail and paid marketing initiatives.

• Partner with marketing teams to design experiments, define KPIs, and measure campaign effectiveness.
• Conduct deep-dive analyses on direct mail and digital media campaigns to extract actionable insights.
• Drive targeting strategy and segmentation using model outputs and historical performance data.

• Ensure models are production-ready using software engineering best practices.
• Monitor and improve model performance over time, integrating results into campaign execution pipelines.

• Work closely with global stakeholders across Data Science, Marketing, Risk, Product, and Engineering.
• Provide thought leadership on applying machine learning to growth and acquisition efforts.
• Translate technical findings into clear, business-impactful recommendations.

• 8+ years of experience in data science with a focus on marketing, growth, or customer acquisition.
• Proven track record developing and deploying predictive models for marketing use cases.
• Strong proficiency in Python and ML libraries (e.g., Scikit-learn, XGBoost, PyTorch, or TensorFlow).
• Advanced SQL skills and experience working with large-scale relational databases.
• Deep understanding of statistical testing, experiment design, and campaign performance analysis.
• Ability to think creatively and move quickly, with a bias for action in a fast-paced environment.
• Exceptional communication skills with the ability to present findings clearly to non-technical stakeholders.
• Masters or Ph.D. in Statistics, Computer Science, Engineering, or a related quantitative field.

• Experience with direct mail targeting, paid media optimization, or acquisition funnel analytics.=
• Background in fintech, credit products, or regulated industries.
• Familiarity with MLOps, particularly in the AWS ecosystem, and workflow tools like Apache Airflow.
• Prior work involving uplift modeling, lookalike modeling, or media mix optimization.

• Excellent group health coverage and life insurance
• Stock options
• Meal allowance
• Transportation assistance (terms and conditions apply)
• Generous paid time off plan, Holidays
• Company-sponsored mental health benefits
• Financial advisory services for both short- and long-term goals
• Learning and development opportunities to support career growth
• Community-based volunteering opportunities