Senior Data Scientist

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. As a Senior Data Scientist in our Bangalore Data Science team, you will operate as an independent problem solver, owning end-to-end development of machine learning solutions powered by our large-scale point-of-sale transaction data. You will navigate ambiguous problem spaces, translate loosely defined business challenges into well-scoped data science problems, and drive them through to measurable impact. You will bring a strong engineering mindset to your work—designing scalable solutions, writing production-quality code, and partnering closely with engineers and architects to deploy robust, reliable models. Beyond model development, you will be responsible for ensuring solutions are production-ready, monitored, and continuously improved. Collaborating cross-functionally with product managers, engineers, and business stakeholders, you will tackle complex problems across the Fintech domain. Your work will directly influence product decisions and drive tangible business outcomes across multiple product lines. A day in the life (Responsibilities) Demonstrated experience in designing and deploying agentic AI workflows and ML/DL solutions in production, with a strong focus on reliability and scalability. Independently lead the  end-to-end lifecycle of machine learning solutions —from problem framing and model development to deployment and impact measurement Collaborate closely with Product, Data Science, ML Engineering, and Platform teams to translate business problems into agent-driven solutions Decompose ambiguous, large-scale problems into  structured, iterative deliverables that drive incremental and measurable business value. Maintain high standards of  code quality, documentation, and reproducibility , enabling scalability and knowledge sharing across the team Stay at the forefront of advancements in AI/ML and bring best practices into the team’s workflows and systems Help in continuing to build out and expand the Data Science and ML Engineering teams Thrive in a fast-paced, evolving environment, balancing  technical rigor with business priorities to deliver sustained impact. What you'll need to thrive (Requirements) Educational Foundation: Advanced degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or a related quantitative field. Experience & Ownership: 6+ years of industry experience in Machine Learning/AI, with a demonstrated ability to independently own and deliver end-to-end data science solutions—from problem framing to production deployment and impact measurement. Core ML Expertise: Strong hands-on experience across supervised and unsupervised learning, including classification, regression, clustering, segmentation, anomaly detection, and predictive modeling. Modeling & Algorithms: Deep proficiency in modern ML techniques such as ensemble and boosting methods (e.g., Random Forest, XGBoost, LightGBM, CatBoost), along with strong foundations in statistical modeling, feature engineering, optimization, and rigorous model evaluation. Advanced Applications: Experience working with advanced ML paradigms including deep learning, time series forecasting, recommendation systems, and handling both structured and unstructured data at scale. Agentic AI in Production: Proven experience designing and deploying agentic or autonomous AI systems in real-world production environments. Engineering Excellence: Strong programming skills in Python and SQL, with experience in tools and frameworks such as Spark, Scala, scikit-learn, TensorFlow, PyTorch, or similar. Ability to write clean, maintainable, production-grade code. Production & MLOps Mindset: Familiarity with software engineering best practices—object-oriented design, testing (TDD), CI/CD, version control (Git), and workflow orchestration (Airflow, Luigi). Experience with cloud ecosystems (preferably AWS, including SageMaker, ECS, DynamoDB) is a strong plus. Cross-functional Collaboration: Ability to work effectively with product managers, engineers, and business stakeholders to identify opportunities, influence decisions, and translate business problems into data-driven solutions. Problem Solving & Communication: Strong analytical mindset with the ability to navigate ambiguity, dive deep into complex datasets, and clearly communicate insights and trade-offs to both technical and non-technical audiences. Bonus ingredients* : Passion for research and curiosity that calls you to go beyond “good enough” to create something innovative and exciting AI at Toast At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across