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**.