Lead Data Scientist

Sequoia; Bengaluru; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

Sequoia in Bengaluru is seeking a Senior Data Scientist to lead the development of ML and advanced analytics architecture for HR, benefits, and payroll products. The successful candidate will have over 12 years of experience in ML development, including designing and deploying complex ML solutions. This role involves leading a team, optimizing algorithms, and building robust MLOps pipelines. A Bachelor's degree in a relevant field is required, alongside expertise in LLMs and time-series forecasting.

Qualifications

• 12+ years of industry experience doing end-to-end ML development on a machine learning team.
• Hands-on experience with LLM pretraining, fine-tuning, and parameter-efficient methods.
• Familiarity with LLM architecture patterns such as RAG and FLARE.

Responsibilities

• Define and own ML architecture for HR, benefits, and payroll products.
• Design end-to-end production-grade ML systems.
• Drive the development and validation of forecasting models.

Skills

Machine learning development

Data ingestion

Feature engineering

Model serving and monitoring

Time-series forecasting

Deep learning

GenAI

CI/CD

Statistical rigor

Team leadership

Education

Bachelor's degree in Computer Science, Engineering, Mathematics or a related field

Tools

Open source LLM foundation models

Vectorized databases

Job description

• Define and own the ML and advanced analytics architecture supporting HR, benefits, 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.


• 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.


• 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.


• 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.

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.


• 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.


• 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.