About OvinAI:
OvinAI is a specialized AI studio that turns promising prototypes into reliable, production-grade autonomous agents for startups. We close the gap between impressive demos and real-world systems by pairing deep expertise in LLMs, RAG, and agentic architectures with robust MLOps, CI/CD, evals, and observability. We ship AI systems engineered for production from day one, with an emphasis on reliability, scalability, and measurable value.
Clients engage through fixed-scope agent builds, hardening of existing prototypes for real-world load, or a fractional AI team model. Teams work directly with the founders from kickoff to production, eliminating handoffs and delivering high-quality execution in weeks, not months.
About the Role:
As a Data Scientist at OvinAI, you’ll design, build, and evaluate the data-driven components that power production-grade autonomous agents. Based on-site in the Bangalore, you’ll explore complex datasets, develop statistical and machine learning models, and work closely with engineering to ship reliable systems.
This is a great fit for someone early in their career (0–2 years) who wants to learn fast and work directly with founders.
Day to day, you will:
• Frame business problems as analytical tasks and run experiments to answer them
• Define, track, and report the metrics that guide product and engineering decisions
• Build dashboards and reports that make complex findings clear and actionable
• Partner with founders and cross-functional teammates to refine data requirements and improve data quality
• Help ensure models are observable, testable, and maintainable in production
• Contribute to internal best practices for experimentation, evaluation, and data governance
What we are looking for:
• 0–2 years of experience in a data science, analytics, or related role (including internships or strong project work)
• Solid foundation in data science and statistics, with the ability to frame problems, design experiments, and interpret results
• Hands-on experience with data analysis to extract insights and validate hypotheses
• Proficiency in data visualization to communicate findings to technical and non-technical audiences
• Proficiency in Python (or a similar language) and familiarity with common libraries such as pandas, NumPy, and scikit-learn
• Experience working with real-world datasets, including cleaning, feature engineering, and handling noisy or incomplete data
• Solid understanding of core machine learning concepts
• Bachelor’s or advanced degree in a quantitative field (Computer Science, Statistics, Mathematics, Engineering) or equivalent practical experience
• Strong communication skills, a collaborative mindset, and ability to work in the remote setting
Nice to have:
• Experience with model training, evaluation, and deployment
• Comfort in a production-oriented environment, collaborating with engineers on testing, monitoring, and CI/CD workflows
