Blend360
Tech / AI / Software
LeadDataScientist
Neural analysis suggests this role is
optimal for mid candidates.
“Lead Data Scientist at Blend360. Skills: Generative AI, LLM, Bayesian modeling, machine learning, AWS SageMaker, Python. 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”
What You'll Achieve.
improve decision-making, efficiency, and growth; quantify uncertainty; support strategic pricing decisions; improve prediction robustness; enhance solution accuracy, scalability, and automation
Industry & Context.
problem-solving skills
What They're Looking For.
Must Have
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, 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, 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), analytical, problem-solving, and communication skills, Ability to work in a fast-paced environment and handle multiple projects
Nice to Have
Experience in A 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
What You'll Do.
Develop and enhance pricing optimization models using statistical
and Generative AI techniques
Analyze pricing elasticity to understand customer behavior and forecast business impact
and deploy Generative AI/LLM-based models (e.g.
for scenario simulation
Use AWS SageMaker for scalable model development
Apply Bayesian modeling approaches to quantify uncertainty
support strategic pricing decisions
and improve prediction robustness
Integrate GenAI tools/frameworks (e.g.
LLM-based automation) into pricing workflows
Continuously explore new GenAI and ML techniques to enhance solution accuracy
How You'll Work.
Team & Collaboration
Work cross-functionally with engineering, product, and business teams to embed data-driven insights into operational processes; working with cross-functional teams
Communication Scope
Communicate complex findings clearly to both technical and non-technical stakeholders; communication skills
Process & Methodology
handle multiple projects
Full Job Description
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. ## Qualifications * 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 i
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