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Staff Data Scientist at OnTrac AI. Role Overview. Lead the design, development, and deployment of advanced machine learning and AI systems that drive measurable business impact. As a senior technical leader, you will define strategy, guide teams, and architect scalable, production-ready models that power innovation across the organization.. Key Responsibilities. • Strategic Leadership: Define and execute the company’s data science and AI roadmap. Provide direction on model development, deployment, and long-term AI capability building.. • Model Development: Architect and deliver predictive, generative, and prescriptive models using advanced machine learning and deep learning techniques.. • AI Platform Engineering: Oversee end-to-end ML pipelines, from data collection and preprocessing to deployment and monitoring in production environments.. • Data Architecture: Ensure data integrity, scalability, and reproducibility across large and complex datasets.. • Mentorship: Build and mentor a high-performing team of data scientists and ML engineers. Promote best practices in experimentation, validation, and continuous learning.. • Innovation: Explore and apply emerging AI methods such as large language models (LLMs), multimodal learning, and reinforcement learning to real-world business problems.. • Stakeholder Engagement: Present analytical insights and model outcomes clearly and persuasively to technical and executive audiences.. Qualifications. • Education: Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.. • Experience: 10+ years in data science, AI, or applied ML, including 3+ years in a senior or staff-level role leading impactful, production-level AI initiatives.. Required Technical Skills. • Expert proficiency in Python and frameworks such as TensorFlow, PyTorch, and scikit-learn.. • Strong foundation in statistical modeling, feature engineering, and end-to-end ML pipeline design.. • Proficiency in SQL and experience with data pipeline orchestration (Airflow, Dataflow, Kubeflow).. • Deep understanding of MLOps, including CI/CD for ML, model serving, and monitoring.. • Familiarity with big data technologies (Spark, Hadoop) and data visualization tools (Tableau, Power BI, Matplotlib).. • Preference for experience or certification with Google Cloud Platform (GCP), including BigQuery, Vertex AI, and Dataflow.. Company Location: India.