• Advanced AI Solution Design & Architecture: Lead the technical design, development, and architecture of cutting-edge AI and Generative AI solutions. This includes selecting appropriate models (LLMs, diffusion models, etc.), designing data pipelines for AI training and inference, and architecting scalable and robust AI systems. • Strategic Client Engagement & Technical Advisory: Serve as a trusted technical advisor to national and international clients, guiding them from strategic planning stages through to the pilot and full-scale implementation of complex AI and GenAI projects. Confidently present and articulate Blend360's technical capabilities and the strategic implications of AI solutions to senior client stakeholders. • Technical Implementation & Oversight: Provide hands-on technical leadership and guidance throughout the entire project lifecycle, from proof-of-concept to pilot and full-scale production deployment. Ensure technical excellence, adherence to best practices, and the delivery of high-quality, performant AI solutions. • Thought Leadership & Innovation: Drive thought leadership in the evolving landscape of GenAI, large language models (LLMs), agentic AI systems, and emerging AI techniques. Research and evaluate new technologies, contribute to internal IP development, and publish insights that position Blend360 at the forefront of AI innovation. • Business Development Support & Technical Scoping: Actively participate in presales activities, providing deep technical expertise for proposal development, solution architecture, and technical scoping. Support the identification and capitalization on new business opportunities by demonstrating our technical capabilities and value proposition. • AI Strategy & Roadmapping: Collaborate with clients to understand their business challenges and translate them into actionable AI strategies and technical roadmaps. Develop bespoke GenAI solutions, facilitate seamless integration, and advise on organizational changes necessary for AI adoption. • Project Leadership & Execution: Lead and manage specific technical workstreams within complex projects, ensuring deliverables meet the strategic goals, technical excellence, and quality standards expected by our clients. Drive cross-functional collaboration with data scientists, machine learning engineers, and other specialists to ensure successful technical outcomes. • Service Evolution & Go-to-Market: Contribute to the continuous development and technical refinement of Blend360's AI and Generative Solutions offerings. Support go-to-market strategies by providing technical insights and expertise for effective positioning in the market.

Req ID: 360897 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Data Engineer Advisor to join our team in Remote, Karnātaka (IN-KA), India (IN). Insurance Domain Experience in Must "Job Duties: Key Responsibilities Data Modeller • Develop and maintain data models-Logical and Physical, to support business needs ensuring data integrity for Insurance domains. • Design models aligned to Databricks medallion architecture by translating the requirements of underwriting ,delegated authority, reinsurance, actuarial, claims and finance. • Implement and maintain modelling standards ,naming conventions, metadata and documentation working closely with data analyst, data engineers, and associates in data office • Review existing models and propose simplification, standardisation and target state improvements across projects and for wider requirements. • Lead the evolution of requirements , refine and translate the specifications into data models to enable development phase • Ensure the models accurately reflect Insurance processes and data elements before handing it over to engineering. Minimum Skills Required: Data Profile • Experience delivering data models for P&C ,Specialty insurance projects with exposure to Lloyd’s/London Market and Syndicate data structures is required . • Understanding of insurance domain concepts and proficiency with data modelling tools(eg Erwin) • Expertise in enterprise data modelling, including conceptual, logical, and physical models for transactional domains • Experience in data modelling using Dimensional Star/Snowflake, Data Vault, and 3NF methodologies. • Knowledge of data warehousing and ETL/ELT pipelines • Experience with Azure Data Factory and Databricks ,designing data pipelines can be advantageous • Understanding and knowledge of system development life cycle methodologies (such as agile software development) • Excellent collaboration and communications skills to deal with senior leaders, stakeholders and technical teams is required • Flexibility and bringing a curious and creative mindset, open to new things and able to propose innovative idea" About NTT DATA NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D. Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us. NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.

• Own the development and deployment of machine learning models to support operational and clinical use cases at Monogram under the guidance of more senior data scientists • Perform ad-hoc data analyses related to outputs or alternative use-cases for existing models (e.g. summarize outputs for reporting purposes) • Work with program owners to understand the goals, key performance measures, and operational details of programs and processes to ensure models are aligned with program intent • Create and present proposals for machine learning solutions to program owners with the aim of ensuring buy-in to proposed solution(s)

• Design and maintain forecasting frameworks for revenue, GMV, merchant growth, and other key business drivers • Lead opportunity sizing for new products, pricing changes, market expansions, and strategic initiatives • Build causal impact measurement capabilities (e.g., synthetic control, diff-in-diff, geo-experiments) to quantify the true ROI of business investments • Develop and maintain a repeatable measurement playbook that standardises how the company evaluates bets — covering incrementality, attribution, and counterfactual reasoning • Create merchant and customer segmentation and scoring models that drive prioritisation across sales, marketing, and merchant success • Define decision-grade metrics and KPIs in partnership with Finance, Commercial, and Product leadership • Translate complex analytical findings into clear, actionable narratives for C-level and cross-functional stakeholders • Mentor analysts and data scientists across the team on statistical methods, causal inference, and analytical rigour