The Impact You'll Drive
We are seeking a
Principal Data Scientist/Engineer who will play a pivotal role in shaping our data-driven strategy, building advanced machine learning solutions, and ensuring scalable data engineering practices. This role requires a strong foundation in
data science & ML, hands-on expertise in
data engineering, and a forward-looking approach toward emerging technologies.
The Hats You Will Wear
- Lead the design, development, and deployment of machine learning models for real-world business problems.
- Drive end-to-end data pipelines, from data ingestion and transformation to model serving and monitoring.
- Collaborate with cross-functional teams to define data strategies, ensuring high-quality, reliable data for analytics and ML use cases.
- Mentor junior data scientists and engineers, setting best practices in modeling, MLOps, and data engineering.
- Explore and evaluate emerging trends in Agentic AI and advanced ML techniques to incorporate into future product capabilities.
- Work closely with product and engineering leadership to align data initiatives with business goals.
The Perfect Fit
- Proven expertise in Data Science & Machine Learning (model development, deployment, and scaling).
- Strong experience in Data Engineering (ETL pipelines, data warehousing, distributed systems).
- Proficiency with Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
- Hands-on experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Kafka, Databricks).
- Solid understanding of MLOps practices (CI/CD for ML, model monitoring, reproducibility).
- Excellent problem-solving, communication, and leadership skills.
Your Edge Over the Rest
- Exposure to Agentic AI frameworks and research in autonomous AI systems.
- Experience with LLMs, prompt engineering, and generative AI.
- Knowledge of advanced optimization and reinforcement learning.
The Problem We're Solving
Financial institutions today are held back by legacy systems that are slow, rigid, and expensive to scale. Launching or evolving credit, lending, and UPI products often takes months, requires heavy engineering effort, and limits the ability to create personalized customer experiences.
At the same time, customer expectations have changed - speed, flexibility, and tailored financial products are no longer optional. Banks and fintechs need infrastructure that allows them to innovate quickly, adapt continuously, and scale without friction.
This is where we come in.
At Vegapay, we are building modern, configurable fintech infrastructure that enables banks, NBFCs, and enterprises to design, launch, and manage credit and payment programs with ease. Our platform brings together flexibility, speed, and control - helping our partners unlock new growth opportunities and deliver personalized banking experiences at scale.
The Opportunity Ahead
- Own and shape the data and ML strategy for high-impact fintech products
- Work on real-world problems at scale across credit, payments, and financial data
- High ownership - from building pipelines to deploying production-grade ML systems
- Opportunity to explore and apply cutting-edge areas like LLMs, Agentic AI, and advanced ML in production
