What You Get to Do:

Technical & Architectural Leadership:

- Define and own the ML and advanced analytics architecture supporting HR, perks, and payroll products.
- Design end-to-end, production-grade ML systems—from data ingestion and feature engineering to model serving, monitoring, and retraining.
- Lead the selection and optimization of algorithms (tree-based models, deep learning, time-

series forecasting, GenAI) with tradeoffs across accuracy, latency, scalability, and cost.
- Establish best practices for model governance, explainability, bias detection, and compliance.

Advanced Modeling & Forecasting:
- Drive the development and validation of time-series and forecasting models

(ARIMA/SARIMA, Prophet, state-space models, LSTM/transformers) for workforce planning,

attrition, and financial forecasting.

- Champion advanced experimentation, model evaluation frameworks, and statistical rigor across teams.
- Leverage GenAI/LLMs where appropriate to enhance product intelligence and user experience.

MLOps & Production Excellence:
- Partner with DevOps and Platform teams to build robust MLOps pipelines using CI/CD,

automated retraining, monitoring, and alerting.
- Ensure reliable, secure,



and scalable model deployment using containerized microservices.
- Define SLAs, performance benchmarks, and operational metrics for ML services in production.

Leadership & Collaboration:
- Lead, mentor, and grow a team of senior and mid-level data scientists, fostering a culture of technical excellence and ownership.
- Work closely with Product, Engineering, Security, and Compliance to translate business needs into scalable ML solutions.
- Act as a trusted advisor to stakeholders, influencing product strategy and long-term data science roadmap.

What You Bring

- 12+ years of industry experience doing end-to-end ML development on a machine learning team and bringing ML models to production
- Familiarity with the setup and use of various open source LLM foundation models.
- Experience with creating and using vectorized databases for data storage and retrieval.
- Familiarity with LLM architecture patterns such as RAG and FLARE.
- Hands on experience with LLM Pretraining, LLM fine-tuning, RLHF, distillation, parameterefficient methods like LoRA, quantization
- Bachelor's degree in Computer Science, Engineering, Mathematics or a related field is required

📌 Lead Data Scientist (Bengaluru)
🏢 Sequoia
📍 Bengaluru