Lead Analyst, Data Science

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities. Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth.

• Develop and enhance pricing optimization models using statistical, machine learning, and Generative AI techniques.
• Analyze pricing elasticity to understand customer behavior and forecast business impact.
• Build, fine-tune, and deploy Generative AI/LLM-based models (e.g., for scenario simulation, automated insights, or decision support).
• Use AWS SageMaker for scalable model development, training, deployment, and monitoring.
• Apply Bayesian modeling approaches to quantify uncertainty, support strategic pricing decisions, and improve prediction robustness.
• Integrate GenAI tools/frameworks (e.g., LangChain, Hugging Face, prompt engineering, LLM-based automation) into pricing workflows.
• Work cross-functionally with engineering, product, and business teams to embed data-driven insights into operational processes.
• Communicate complex findings clearly to both technical and non-technical stakeholders.
• Continuously explore new GenAI and ML techniques to enhance solution accuracy, scalability, and automation.

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Economics, or related fields.
• 5–8 years of hands-on experience in Data Science, including pricing analytics or predictive modeling.
• Strong foundation in Generative AI, with experience in LLM fine-tuning, embeddings, or workflow orchestration.
• Expertise in Bayesian modeling and applied machine learning.
• Proven experience with AWS SageMaker for model lifecycle management.
• Strong programming skills in Python (preferred) or R.
• Experience with GenAI frameworks and libraries (e.g., LangChain, Hugging Face Transformers, PyTorch, TensorFlow).
• Proficiency with data and statistical libraries such as NumPy, Pandas, PyMC3 (or similar).
• Strong analytical, problem-solving, and communication skills.
• Ability to work in a fast-paced environment and handle multiple projects.

 Preferred Qualifications

• Experience in A/B testing, econometrics, or other experimentation techniques.
• Exposure to other cloud platforms (Azure, GCP).
• Experience in client-facing roles or working with cross-functional teams.
• Knowledge of AWS Data Analytics – Specialty certification is a plus.