Staff Data Scientist

Staff Data Scientist

It is a global B2B SaaS platform.

Job Summary

The role involves taking ownership of innovative AI and machine learning solutions, leading a talented team, and shaping the technical vision for next-generation marketing platforms. The candidate will work on cutting-edge technologies such as Large Language Models (LLMs), classical ML models, and AI agents, contributing to the company's mission of building scalable, impactful solutions for a user base of over 900 million active users.

Responsibilities

• Architect and develop production-grade AI and ML solutions with a focus on rapid prototyping, robustness, scalability, and outcome ownership.
• Spearhead the design and implementation of classical ML models, reinforcement learning, multi-arm bandits, and LLM-based models to enhance product features such as user behavior prediction and recommendation systems.
• Lead deep technical code reviews and design sessions to ensure high-quality, scalable, and innovative outputs.
• Stay at the forefront of LLM and AI agent research, guiding the team on adopting new models, techniques, and frameworks.
• Mentor and lead a team of data scientists, fostering their professional growth through coaching, guidance, and active involvement in project execution.
• Define and execute the end-to-end technical vision for integrating predictive signals and generative AI capabilities into the company's marketing platform.
• Collaborate with Product and Engineering leadership to translate business goals into technical requirements and develop a clear project roadmap.
• Drive projects from concept to deployment, ensuring models are accurate, scalable, efficient, and maintainable.
• Develop and implement offline and online evaluation frameworks (including A/B testing) to measure and optimize recommendation quality and business impact.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 10-12 years of hands-on experience in building and deploying machine learning models in a business environment.
• 2+ years of experience in a tech lead or management role.
• Proven expertise in designing and deploying classical ML models (e.g., XGBoost, Logistic Regression) and Large Language Models (LLMs).
• Proficiency in Python, SQL, and data science libraries such as pandas, NumPy, scikit-learn, XGBoost, Spark.
• Demonstrated success in leading complex end-to-end data science projects with significant business impact.
• Strong understanding of ML deployment, scalability, and production best practices.

Preferred Skills

• Experience with cloud-based ML platforms and ML Ops tools such as AWS SageMaker, MLflow, Ray, Feature Platform.
• Familiarity with frameworks like LangChain, LlamaIndex, or Agent Development Kits for building LLM applications.
• Knowledge of LLM operational concerns, including cost management, latency optimization, and responsible AI principles (bias, fairness, safety).
• Experience in building systems that combine predictive and generative models working in concert.

Experience

• 10-12 years of relevant experience in machine learning, data science, or AI.
• 2+ years in a leadership capacity, managing teams and projects.

Environment

• The role involves working in a collaborative, fast-paced environment focused on innovation and scaling.
• The position may be remote, in-office, or hybrid, depending on company policies.
• The work involves engaging with cutting-edge AI research, large-scale data processing, and cross-functional collaboration.