Lead Data Scientist driving ML and data science initiatives for advertising technology at Disney. Collaborating with a team to enhance ad decisioning and user experience optimization with generative AI.
About the role
- Staff Engineer pivotal for AI-driven enterprise revenue solutions at Clari + Salesloft. Join a growing team in Bengaluru contributing to cutting-edge cloud-based technologies.
Responsibilities
- Define the long-term roadmap for our Applied AI stack
- Lead the design and implementation of production-grade Agentic workflows and RAG systems
- Own the core revenue models (Forecasting, Deal Health, Churn Prediction)
- Write high-quality, reusable Python code
- Partner with Product and Engineering leadership to translate vague business objectives into concrete technical specifications
- Mentor senior data scientists, conduct code/design reviews
- Contribute actively to internal documentation, onboarding, and training programs
Requirements
- 10+ years in Data Science or Machine Learning, with a proven track record of shipping AI products at scale (Staff/Lead experience preferred)
- Deep expertise in Classical ML (XGBoost, Causal Inference), Time-Series Forecasting, and Deep Learning fundamentals
- Practical experience building with LLMs in production
- Proficiency with modern frameworks (LangChain, LlamaIndex, DSPy), vector databases (Pinecone, Milvus)
- Expert-level proficiency in Python and SQL
- Ability to design end-to-end ML systems
- MS or PhD in Computer Science, Statistics, Physics, Math, or equivalent quantitative field is preferred
Benefits
- Equal Opportunity Employer
- Inclusive and supportive workplace
- Employment opportunities to all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, pregnancy, or any other characteristic protected by law
- AI notetaker in interviews
- Use of AI tools to assist in hiring process
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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