Manager, Data Science

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 establishing a pioneering data science team in India and are seeking a highly skilled Data Science Manager to drive our efforts. In this role, you will lead a team of data scientists, guiding their work while also remaining hands-on with advanced data science tasks. You will play a crucial role in developing and implementing sophisticated models, coordinating with the group lead, and ensuring alignment with our strategic goals.

Key Responsibilities:

• Team Leadership & Development: Lead and mentor a team of 2 individual contributors (ICs), providing guidance on project execution, technical challenges, and professional growth. Foster a collaborative and innovative team environment.
• Hands-on Modeling & Analytics: Apply your expertise in advanced statistical, machine learning, and predictive modeling techniques to design, build, and improve decision-making systems. Set the standard for technical excellence within the team.
• Project Management: Manage and oversee data science projects from concept to deployment, ensuring timely delivery of high-quality solutions. Allocate resources effectively and prioritize tasks to align with business objectives.
• Stakeholder Communication: Serve as the primary point of contact between your team and the group lead. Communicate progress, challenges, and insights clearly and effectively, ensuring alignment with broader organizational goals.
• MLOps & System Integration: Lead efforts to maintain and enhance the data science infrastructure, integrating new technologies and practices into our workflows. Ensure that models are robust, scalable, and maintainable.
• Strategic Data Collection: Oversee initiatives to develop and implement data collection strategies that support advanced analytics and model development. Ensure that data pipelines are efficient and reliable.

• 7+ Years of Experience: A minimum of 7 years of experience in data science, with at least 2 years in a leadership or managerial role. Demonstrated experience in leading teams and delivering complex data-driven solutions.
• Expertise in Python: Extensive experience in developing and deploying production-level code in Python, with a deep understanding of machine learning frameworks such as Scikit-learn, PyTorch, TensorFlow, or similar.
• Strong SQL and Database Knowledge: Proficiency in working with relational databases, writing optimized SQL queries, and managing large-scale datasets.
• Comprehensive ML Lifecycle Experience: Proven ability to manage the entire lifecycle of ML model development, from ideation and experimentation to deployment and monitoring in a production environment.
• Analytical & Strategic Thinking: Ability to analyze complex data sets, derive actionable insights, and communicate these insights effectively to both technical and non-technical stakeholders.
• Educational Background: A Masters or Ph.D. in Statistics, Computer Science, Engineering, or a related quantitative field is preferred.
• Proven Leadership Skills: Demonstrated ability to lead a team, manage multiple priorities, and work effectively across functions and geographies.

• Cross-Functional Collaboration: Experience working with Data/MLOps Engineering, Analytics, Business, and Product teams in a collaborative environment.
• Domain Specialization: Expertise in areas like fraud detection, credit risk prediction, or graph models and analytics.
• MLOps & Cloud Infrastructure: Hands-on experience with MLOps, particularly within the AWS ecosystem, and familiarity with orchestration tools like Apache Airflow.
• Experimentation & Impact Analysis: Skilled in designing experiments and analyzing their outcomes to measure the impact and effectiveness of data-driven solutions.

• Excellent group health coverage and life insurance
• Stock options
• Hybrid work model
• 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