Total 6 job vacancies by Blend360

We are seeking a highly skilled Senior Data Scientist with deep expertise in Generative AI to design, develop, and deploy innovative AI solutions that drive measurable business impact. This role requires a combination of strong data science fundamentals, hands-on experience with LLMs, NLP, and generative modeling, and a proven ability to build scalable, production-ready systems.

As a key member of our Data Science & AI team, you will spearhead the development of advanced analytics and GenAI-driven solutions across multiple business functions, including:

• Product Assortment and Pricing Optimization
• Supply Chain Optimization
• Demand Forecasting
• Propensity, Loyalty & Customer Segmentation Models
• Recommendation Engines & Personalization
• Marketing Mix Modeling (MMM) & Media Investment Optimization (MIO)

You will apply Regression, Bayesian modeling, Classification, Time Series forecasting, Deep Learning, and Generative AI to power actionable predictions and insights — while expanding AI capabilities into:

• Computer Vision solutions such as object detection/recognition, product imagery analysis
• Image-to-Text modeling, document intelligence, OCR, and multi-modal LLM applications

Key Responsibilities:

• Architect, train, and deploy generative AI models, including large language models (LLMs) and transformer-based systems.
• Develop robust predictive and optimization models using structured and unstructured data sources.
• Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment.
• Partner with cross-functional teams to translate business requirements into scalable AI solutions.
• Drive model lifecycle management from research and experimentation through deployment and monitoring.
• Maintain high standards for model governance, explainability, performance, and ethical AI.
• Stay at the forefront of GenAI advancements and proactively evaluate new tools, methods, and frameworks.

We are seeking a highly skilled Senior Data Scientist with deep expertise in Generative AI to design, develop, and deploy innovative AI solutions that drive measurable business impact. This role requires a combination of strong data science fundamentals, hands-on experience with LLMs, NLP, and generative modeling, and a proven ability to build scalable, production-ready systems.

As a key member of our Data Science & AI team, you will spearhead the development of advanced analytics and GenAI-driven solutions across multiple business functions, including:

• Product Assortment and Pricing Optimization
• Supply Chain Optimization
• Demand Forecasting
• Propensity, Loyalty & Customer Segmentation Models
• Recommendation Engines & Personalization
• Marketing Mix Modeling (MMM) & Media Investment Optimization (MIO)

You will apply Regression, Bayesian modeling, Classification, Time Series forecasting, Deep Learning, and Generative AI to power actionable predictions and insights — while expanding AI capabilities into:

• Computer Vision solutions such as object detection/recognition, product imagery analysis
• Image-to-Text modeling, document intelligence, OCR, and multi-modal LLM applications

Key Responsibilities:

• Architect, train, and deploy generative AI models, including large language models (LLMs) and transformer-based systems.
• Develop robust predictive and optimization models using structured and unstructured data sources.
• Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment.
• Partner with cross-functional teams to translate business requirements into scalable AI solutions.
• Drive model lifecycle management from research and experimentation through deployment and monitoring.
• Maintain high standards for model governance, explainability, performance, and ethical AI.
• Stay at the forefront of GenAI advancements and proactively evaluate new tools, methods, and frameworks.

We are seeking a highly skilled Senior Data Scientist with deep expertise in Generative AI to design, develop, and deploy innovative AI solutions that drive measurable business impact. This role requires a combination of strong data science fundamentals, hands-on experience with LLMs, NLP, and generative modeling, and a proven ability to build scalable, production-ready systems.

As a key member of our Data Science & AI team, you will spearhead the development of advanced analytics and GenAI-driven solutions across multiple business functions, including:

• Product Assortment and Pricing Optimization
• Supply Chain Optimization
• Demand Forecasting
• Propensity, Loyalty & Customer Segmentation Models
• Recommendation Engines & Personalization
• Marketing Mix Modeling (MMM) & Media Investment Optimization (MIO)

You will apply Regression, Bayesian modeling, Classification, Time Series forecasting, Deep Learning, and Generative AI to power actionable predictions and insights — while expanding AI capabilities into:

• Computer Vision solutions such as object detection/recognition, product imagery analysis
• Image-to-Text modeling, document intelligence, OCR, and multi-modal LLM applications

Key Responsibilities:

• Architect, train, and deploy generative AI models, including large language models (LLMs) and transformer-based systems.
• Develop robust predictive and optimization models using structured and unstructured data sources.
• Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment.
• Partner with cross-functional teams to translate business requirements into scalable AI solutions.
• Drive model lifecycle management from research and experimentation through deployment and monitoring.
• Maintain high standards for model governance, explainability, performance, and ethical AI.
• Stay at the forefront of GenAI advancements and proactively evaluate new tools, methods, and frameworks.

• 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.

• 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.

We are looking for an experienced Snowflake Manager to lead a high-performing team of data engineers, own client relationships, and drive end-to-end cloud data platform strategy. The ideal candidate brings deep expertise in Snowflake, AWS, and Python, with hands-on experience across data lake and clean room architecture, identity resolution, ETL/ELT pipelines, and MLOps. This role requires someone equally strong in technical leadership and people management — setting direction, delivering through teams, and ensuring referenceable outcomes for stakeholders.

Key Responsibilities

• Directly manage a team of data engineers — overseeing performance, career development, and team dynamics; leading multiple concurrent projects to scope, timeline, and quality; and delivering constructive feedback with support from senior leadership.
• Own client and stakeholder relationships within assigned accounts, ensuring referenceable outcomes and managing nonstandard situations with senior support where needed.
• Design and implement Snowflake data warehouse architecture, data lake, and clean room frameworks, including identity resolution strategies, ID join logic, and master lookup tables across heterogeneous data sources.
• Build and maintain core data tables and ETL/ELT pipelines from multiple source types (network, device, media/video), covering ingestion, transformation, and data quality validation.
• Architect AWS cloud data solutions (S3, Glue, Kinesis, Lambda, Step Functions), including dev/prod environment setup, CI/CD pipelines, and workflow orchestration via Airflow or AWS-native services.
• Drive MLOps, pipeline automation, and platform reliability — including Snowflake performance tuning, storage optimisation, capacity planning, and onboarding of new data sources.
• Enforce data governance, security, and privacy standards across all pipelines, including AWS IAM policies, encryption, and data quality controls.
• Collaborate with analysts, product, and business stakeholders to translate requirements into efficient data models and solutions.