Description :

Who We Are :

For more than 24 years, people-driven companies have turned to Sequoia to get their employee experience right. We are in this business because we know that taking great care of people leads to better business outcomes. Helping our clients achieve those outcomes is what drives our team, our strategic service offerings, and our technology forward.

Sequoia comes through for clients with guidance, service, and the Sequoia People Platform. Through their compensation, benefits, and overall people programs, we enable them to better manage their global workforce, reduce administrative burdens, and reach a deeper level of employee care and support. We strategically use technology to enhance the expert guidance and committed service we bring to every client engagement.

Role Overview :

As a Lead Data Scientist, you will provide technical leadership and strategic direction for Sequoia's core machine learning and advanced analytics platforms. You will architect, build, and scale enterprise ML services while mentoring high-performing data science teams and influencing product and business strategy through data-driven insights. This role combines hands-on technical depth and close partnership with Product and Engineering leadership to deliver measurable business impact.

What You Get to Do :

Technical & Architectural Leadership :

- Define and own the ML and advanced analytics architecture supporting HR, benefits, and payroll products.

- Design end-to-end, production-grade ML system?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 :

- 11+ 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, parameter-efficient methods like LoRA, quantization

- Experience with observability, monitoring, debugging, and performance evaluation for LLM training / inference systems.

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

Sequoia's Culture : Our most important asset

- Integrity

- Passion for service

- Innovative

- Growth oriented

- Caring for others

- Promise-centric

- Focused on relationship building

Sequoia Consulting Group provides equal opportunity to all applicants without regard to race, color, creed, religion, citizenship, national origin, age, sex, sexual orientation, gender identity, pregnancy, marital status, military or veteran status, disability, or any other basis prohibited by applicable law.