104 Aws Sagemaker Jobs

Dear Candidate, We are seeking a Machine Learning Engineer to develop predictive models and deploy them into production. Ideal for professionals passionate about AI and data science. Key Responsibilities: Develop and train machine learning models Preprocess and analyze large datasets Deploy models using scalable infrastructure Collaborate with product teams to integrate ML solutions Required Skills & Qualifications: Strong knowledge of Python and ML libraries (scikit-learn, TensorFlow, PyTorch) Experience with data preprocessing and feature engineering Familiarity with model deployment techniques Bonus: Experience with cloud ML services (AWS SageMaker, Google AI Platform) Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

*****GenAI DevOps Engineer AWS Bedrock***** *****Pune Hinjewadi***** *****Immediate Joiners Preferred***** *****Minimum 4 Days WFO***** Job Description: We are seeking a highly experienced GenAI DevOps Engineer to join our dynamic team in Pune. The ideal candidate will have a strong background in building, deploying, and optimizing Generative AI applications on AWS Bedrock, along with expertise in DevOps practices. You will be responsible for automating infrastructure, managing CI/CD pipelines, and ensuring high performance and reliability of AI models. Key Responsibilities: Design, develop, and deploy Generative AI applications leveraging AWS Bedrock and SageMaker. Automate infrastructure provisioning and deployment processes. Build and maintain robust CI/CD pipelines using CodePipeline and CodeBuild. Monitor application and model performance using CloudWatch, Prometheus, and Grafana. Optimize AI models for performance, scalability, and cost-efficiency. Work with RAG (Retrieval-Augmented Generation) tools such as LangChain, Haystack, and LlamaIndex for building advanced AI solutions. Collaborate with data scientists and developers to streamline model deployment and monitoring. Required Skills: Extensive hands-on experience with AWS Bedrock and SageMaker. Strong expertise in CI/CD tools: CodePipeline, CodeBuild. Proficiency with monitoring tools: CloudWatch, Prometheus, Grafana. Experience with RAG frameworks like LangChain, Haystack, and LlamaIndex. Solid understanding of DevOps best practices and automation. Ability to troubleshoot and optimize AI deployment pipelines. Excellent problem-solving and communication skills. Preferred Skills: Knowledge of containerization (Docker, Kubernetes). Familiarity with scripting languages (Python, Bash). Experience with cloud security best practices. Understanding of machine learning lifecycle management. Mandatory Skills: AWS Bedrock and SageMaker expertise. CI/CD pipeline automation. Monitoring and performance optimization. RAG-based application development.

Job Title: AWS Data Engineer Role Overview: We are seeking a skilled AWS Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, with a focus on building and maintaining scalable data pipelines and infrastructure using AWS services. Key Responsibilities: Design and Implement Data Pipelines: Develop and maintain scalable data pipelines using AWS Glue, Lambda, and other AWS services. Data Storage and Management: Manage data lakes on AWS S3, ensuring efficient data storage and retrieval. ETL Processes: Automate ETL (Extract, Transform, Load) processes using AWS Step Functions and Apache Airflow. Collaboration: Work closely with data scientists to optimize machine learning models on AWS SageMaker. Data Security: Ensure data security and compliance with AWS IAM (Identity and Access Management) and KMS (Key Management Service) policies. Performance Tuning: Optimize performance of data processing and storage solutions. Qualifications: Educational Background: Bachelor's degree in computer science, Information Technology, or a related field. Experience: Proven experience as a Data Engineer, with a focus on AWS services. Technical Skills: Proficiency in AWS services such as Glue, Lambda, S3, Redshift, RDS (Postgres, MySql). Strong programming skills in Python, SQL, and other relevant languages. Problem-Solving: Strong analytical and problem-solving skills, with the ability to work in a fast-paced environment. Communication: Excellent communication and teamwork skills. Preferred Qualifications: Certifications: AWS Certified Data Analytics - Specialty or AWS Certified Data Engineer

Looking for a Sr MLOps Engineer with a strong background in Data Engineering, who aspire to be part of a Data Science & AI Operations function in R&D. This role involves applying advanced software engineering skills for the design, creation, management, and business use of large datasets, across a variety of Data/ML platforms. This is an ideal opportunity for individuals with a passion for applying DevOps Skills for AI/ML application development in the health-care sector. Preferred Requirements: M.S (preferred) or Ph.D. in Computer Science, Data Science, or related quantitative fields. Proven experience in applying advanced software engineering skills in Data Science platforms (Data/ML) Strong experience in using MLOps tools like AWS SageMaker, MLFlow and ML Frameworks like TensorFlow/PyTorch Hands-on Experience in CI/CD using tools Terraform/CloudFormation, Git, Containers Docker/Kubernetes, ECS/EKS, Helm Charts Strong knowledge and Hands-on Experience with Data Lakes in building Data Pipelines using Python, Apache Spark, Lambda, Step Functions, SQL, Glue ETL in AWS Working knowledge on Cloud Platforms & Infrastructure in AWS Programming and Scripting knowledge using Python (Must needed), CLI/SDK/CDK Ability to balance between Development and Research work on latest trends (GenAI Ops) Minimum Requirements: Master's Degree or Higher in Computer Science/Data Science The ability to fluently read, write, understand, and communicate in English. Relevant AWS Certifications related to ML/Data /Data (preferred) 3+ years of hands-on working experience in applying MLOps engineering for Data/AI with real-world problem solving in the medical device industry or equivalent industry experience is preferred.

As an Applied AI Engineer, you will work at the intersection of AI research and practical implementation. You will develop machine learning (ML) and deep learning (DL) models, integrate them into our SaaS platform, and optimize them for scalability, performance, and business impact. Key Responsibilities: Data Engineering & Feature Engineering: Work with structured and unstructured data to build high-quality datasets. Develop robust feature engineering pipelines to improve model accuracy. Implement data preprocessing and augmentation techniques. MLOps & AI Infrastructure: Build and maintain ML pipelines for continuous integration and deployment (CI/CD). Implement model monitoring, retraining, and performance tracking frameworks. Work with cloud platforms (AWS, GCP, Azure) for AI model deployment and scaling. AI Integration in SaaS Applications: Collaborate with software engineers to integrate AI models into customer-facing SaaS products. Develop APIs and microservices for seamless AI-powered functionalities. Optimize inference performance for real-time and batch processing scenarios. Collaboration & Research: Stay updated with the latest AI research and bring innovative solutions to production. Work closely with product managers, designers, and engineers to align AI capabilities with business goals. Participate in code reviews, knowledge sharing, and AI/ML best practices. Prompt Engineering: Design, develop, and refine AI-generated text prompts for various applications to ensure accuracy, engagement, and relevance Craft and optimize prompts that guide our AI systems to generate accurate, informative, and creative outputs Build accessible libraries of prompts, keywords, and syntax guidelines for optimal query results Develop robust evaluation frameworks to assess AI model performance and prompt effectiveness Test and analyze outputs by experimenting with different prompts and measuring against defined metrics Create dashboards and reporting tools to track AI performance across multiple dimensions Apply human judgment to identify gaps in AI-generated output and refine prompts accordingly Implement continuous improvement processes based on evaluation insights What Were Looking For: Experience: 5-6 years in AI/ML engineering, with hands-on experience in Generative AI, NLP and deploying AI solutions at scale. Technical Expertise: Strong background in machine learning, deep learning, and NLP. Proficiency in Python Help assess performance metrics, develop novel agent frameworks, create and oversee data workflows, and conduct extensive testing to deploy innovative capabilities. Ship with high intent and work with the team to improve your ability to iterate and ship AI-powered features over time. Experience with data processing tools (Pandas, NumPy, Spark, Dask). Familiarity with MLOps, CI/CD, and cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML). AI Deployment & Optimization: Experience with optimizing models for performance, interpretability, and real-time applications. Strong Problem-Solving Skills: Ability to translate business problems into AI-driven solutions. SaaS Experience (Preferred): Understanding of how AI enhances SaaS applications and workflows.

AWS AI/ML Expert with 5 to 6 years of hands on experience in designing, developing, and deploying artificial intelligence and machine learning solutions on the AWS cloud platform. The ideal candidate will have strong proficiency in AWS AI services

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and Inviting applications for the role of Principal Consultant -Lead MLOps Engineer! In this role, you will define, implement and oversee the MLOps strategy for scalable, compliant, and cost-efficient deployment of AI/ GenAI models across the enterprise. This role combines deep DevOps knowledge, infrastructure architecture, and AI platform design to guide how teams build and ship ML models securely and reliably. You will establish governance, reuse, and automation frameworks for AI infrastructure, including Terraform-first cloud automation, multi-environment CI/CD, and observability pipelines. Responsibilities Architect secure, reusable, modular IaC frameworks across cloud and regions for MLOps Lead the development of CI/CD pipelines and standardize deployment frameworks. Design observability and monitoring systems for ML/ GenAI workloads. Collaborate with platform, data science, compliance and Enterprise Architecture teams to ensure scalable ML operations. Define enterprise-wide MLOps architecture and standards (build ? deploy ? monitor) Lead design of GenAI / LLMOps platform (Bedrock/OpenAI/Hugging Face + RAG stack) Integrate governance controls (approvals, drift detection, rollback strategies) Define model metadata standards, monitoring SLAs, and re-training workflows Influence tooling, hiring, and roadmap decisions for AI/ML delivery Be engaging in the design, development and maintenance of data pipelines for various AI use cases Required to actively contribution to key deliverables as part of an agile development team Qualifications we seek in you! Minimum Qualifications Good years of experience in DevOps or MLOps roles. Degree/qualification in Computer Science or a related field, or equivalent work experience Strong Python programming skills. Hands on experience in containerised deployment. Proficient with AWS (SageMaker, Lambda, ECR), Terraform, and Python. Demonstrated experience deploying multiple GenAI systems into production. Hands-on experience deploying 3-4 ML/ GenAI models in AWS. Deep understanding of ML model lifecycle: train ? test ? deploy ? monitor ? retrain. Experience in developing, testing, and deploying data pipelines using public cloud. Clear and effective communication skills to interact with team members, stakeholders and end users Knowledge of governance and compliance policies, standards, and procedures Exposure to RAG/LLM workloads and model deployment infrastructure. Experience in developing, testing, and deploying data pipelines Preferred Qualifications/ Skills Experience designing model governance frameworks and CI/CD pipelines. Knowledge of governance and compliance policies, standards, and procedures Advanced understanding of platform security, cost optimization, and ML observability. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

As Lead ML Engineer , you'll lead the development of predictive models for demand forecasting, customer segmentation, and retail optimization, from feature engineering through deployment. As Lead ML Engineer, you'll lead the development of predictive models for demand forecasting, customer segmentation, and retail optimization, from feature engineering through deployment. Responsibilities: Build and deploy models for forecasting and optimization Perform time-series analysis, classification, and regression Monitor model performance and integrate feedback loops Use AWS SageMaker, MLflow, and explainability tools (e.g., SHAP or LIME)

Role : MLOps Engineer Location – PAN India Notice: Immediate to 60 days Key words -Skillset AWS SageMaker, Azure ML Studio, GCP Vertex AI PySpark, Azure Databricks MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline Kubernetes, AKS, Terraform, Fast API Responsibilities Model Deployment, Model Monitoring, Model Retraining Deployment pipeline, Inference pipeline, Monitoring pipeline, Retraining pipeline Drift Detection, Data Drift, Model Drift Experiment Tracking MLOps Architecture REST API publishing Job Responsibilities: Research and implement MLOps tools, frameworks and platforms for our Data Science projects. Work on a backlog of activities to raise MLOps maturity in the organization. Proactively introduce a modern, agile and automated approach to Data Science. Conduct internal training and presentations about MLOps tools’ benefits and usage. Required experience and qualifications: Wide experience with Kubernetes. Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube). Good understanding of ML and AI concepts. Hands-on experience in ML model development. Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit. Experience in CI/CD/CT pipelines implementation. Experience with cloud platforms - preferably AWS - would be an advantage.

The Data Scientist organization within the Data and Analytics division is responsible for designing and implementing a unified data strategy that enables the efficient, secure, and governed use of data across the organization. We aim to create a trusted and customer-centric data ecosystem, built on a foundation of data quality, security, and openness, and guided by the Thomson Reuters Trust Principles. Our team is dedicated to developing innovative data solutions that drive business value while upholding the highest standards of data management and ethics. About the role: Work with low to minimum supervision to solve business problems using data and analytics. Work in multiple business domain areas including Customer Experience and Service, Operations, Finance, Sales and Marketing. Work with various business stakeholders, to understand and document requirements. Design an analytical framework to provide insights into a business problem. Explore and visualize multiple data sets to understand data available for problem solving. Build end to end data pipelines to handle and process data at scale. Build machine learning models and/or statistical solutions. Build predictive models. Use Natural Language Processing to extract insight from text. Design database models (if a data mart or operational data store is required to aggregate data for modeling). Design visualizations and build dashboards in Tableau and/or PowerBI Extract business insights from the data and models. Present results to stakeholders (and tell stories using data) using power point and/or dashboards. Work collaboratively with other team members. About you: Overall 3+ years' experience in technology roles. Must have a minimum of 1 years of experience working in the data science domain. Has used frameworks/libraries such as Scikit-learn, PyTorch, Keras, NLTK. Highly proficient in Python. Highly proficient in SQL. Experience with Tableau and/or PowerBI. Has worked with Amazon Web Services and Sagemaker. Ability to build data pipelines for data movement using tools such as Alteryx, GLUE, Informatica. Proficient in machine learning, statistical modelling, and data science techniques. Experience with one or more of the following types of business analytics applications: Predictive analytics for customer retention, cross sales and new customer acquisition. Pricing optimization models. Segmentation. Recommendation engines. Experience in one or more of the following business domains Customer Experience and Service. Finance. Operations. Good presentation skills and the ability to tell stories using data and PowerPoint/Dashboard Visualizations. Excellent organizational, analytical and problem-solving skills. Ability to communicate complex results in a simple and concise manner at all levels within the organization. Ability to excel in a fast-paced, startup-like environment. #LI-SS5 Whats in it For You Hybrid Work Model Weve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected. Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrows challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future. Industry Competitive Benefits We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing. Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our valuesObsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together. Social Impact Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound excitingJoin us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here. Learn more on how to protect yourself from fraudulent job postings here. More information about Thomson Reuters can be found on thomsonreuters.com.

About the Role: Grade Level (for internal use): 13 Location: Gurgaon, Hyderabad and Bangalore : We are seeking a highly skilled and visionary Agentic AI Architect to lead the strategic design, development, and scalable implementation of autonomous AI systems within our organization. This role demands an individual with deep expertise in cutting-edge AI architectures, a strong commitment to ethical AI practices, and a proven ability to drive innovation. The ideal candidate will architect intelligent, self-directed decision-making systems that integrate seamlessly with enterprise workflows and propel our operational efficiency forward. Key Responsibilities As an Agentic AI Architect, you will: AI Architecture and System Design: Architect and design robust, scalable, and autonomous AI systems that seamlessly integrate with enterprise workflows, cloud platforms, and advanced LLM frameworks. Define blueprints for APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Strategic AI Leadership: Provide technical leadership and strategic direction for AI initiatives focused on agentic systems. Guide cross-functional teams of AI engineers, data scientists, and developers in the adoption and implementation of advanced AI architectures. Framework and Platform Expertise: Evaluate, recommend, and implement leading AI tools and frameworks, with a strong focus on autonomous AI solutions (e.g., multi-agent frameworks, self-optimizing systems, LLM-driven decision engines). Drive the selection and utilization of cloud platforms (AWS SageMaker preferred, Azure ML, Google Cloud Vertex AI) for scalable AI deployments. Customization and Optimization: Design strategies for optimizing autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Define methodologies for fine-tuning LLMs, multi-agent frameworks, and feedback loops to align with overarching business goals and architectural principles. Innovation and Research Integration: Spearhead the integration of R&D initiatives into production architectures, advancing agentic AI capabilities. Evaluate and prototype emerging frameworks (e.g., Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems for architectural viability. Documentation and Architectural Blueprinting: Develop comprehensive technical white papers, architectural diagrams, and best practices for autonomous AI system design and deployment. Serve as a thought leader, sharing architectural insights at conferences and contributing to open-source AI communities. System Validation and Resilience: Design and oversee rigorous architectural testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation strategies, ensuring alignment with compliance, ethical and performance benchmarks for robust production systems. Stakeholder Collaboration & Advocacy: Collaborate with executives, product teams, and compliance officers to align AI architectural initiatives with strategic objectives. Advocate for AI-driven innovation and architectural best practices across the organization. Qualifications: Technical Expertise: 12+ years of progressive experience in AI/ML, with a strong track record as an AI Architect , ML Architect, or AI Solutions Lead. 7+ years specifically focused on designing and architecting autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js for architectural integrations. Extensive hands-on experience with autonomous AI tools and frameworks LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Proficiency in cloud platforms for AI architecture AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI, with a deep understanding of their AI service offerings. Demonstrable experience with MLOps pipelines (e.g., Kubeflow, MLflow) and designing scalable deployment strategies for AI agents in production environments. Leadership & Strategic Acumen: Proven track record of leading the architectural direction of AI/ML teams, managing complex AI projects, and mentoring senior technical staff. Strong understanding and practical application of AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and advanced bias mitigation techniques within AI architectures. Exceptional ability to translate complex technical AI concepts into clear, concise architectural plans and strategies for non-technical stakeholders and executive leadership. Ability to envision and articulate a long-term strategy for AI within the business, aligning AI initiatives with business objectives and market trends. Foster collaboration across various practices, including product management, engineering, and marketing, to ensure cohesive implementation of AI strategies that meet business goals. Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority Ratings - (Strategic Workforce Planning)

About the Role: Grade Level (for internal use): 12 Lead Agentic AI Developer LocationGurgaon, Hyderabad and Bangalore : A Lead Agentic AI Developer will drive the design, development, and deployment of autonomous AI systems that enable intelligent, self-directed decision-making. Their day-to-day operations focus on advancing AI capabilities, leading teams, and ensuring ethical, scalable implementations. Responsibilities AI System Design and Development Architect and build autonomous AI systems that integrate with enterprise workflows, cloud platforms, and LLM frameworks. Develop APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Team Leadership and Mentorship Lead cross-functional teams of AI engineers, data scientists, and developers. Mentor junior staff in agentic AI principles, reinforcement learning, and ethical AI governance. Customization and Advancement Optimize autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Fine-tune LLMs, multi-agent frameworks, and feedback loops to align with business goals. Ethical AI Governance Monitor AI behavior, audit decision-making processes, and implement safeguards to ensure transparency, fairness, and compliance with regulatory standards. Innovation and Research Spearhead R&D initiatives to advance agentic AI capabilities. Experiment with emerging frameworks (e.g.,Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems. Documentation and Thought Leadership Publish technical white papers, case studies, and best practices for autonomous AI. Share insights at conferences and contribute to open-source AI communities. System Validation Oversee rigorous testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation. Validate alignment with ethical and performance benchmarks. Stakeholder Leadership Collaborate with executives, product teams, and compliance officers to align AI initiatives with strategic objectives. Advocate for AI-driven innovation across the organization. What Were Looking For : REQUIRED S/QUALIFICATIONS Technical Expertise : 8+ years as a Senior AI Engineer , ML Architect , or AI Solutions Lead , with 5+ years focused on autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js . Hands-on experience with autonomous AI tools LangChain, Autogen, CrewAI, or custom agentic frameworks. Proficiency in cloud platforms AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI. Experience with MLOps pipelines (e.g., Kubeflow, MLflow) and scalable deployment of AI agents. Leadership Proven track record of leading AI/ML teams, managing complex projects, and mentoring technical staff. Ethical AI Familiarity with AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and bias mitigation techniques. Communication Exceptional ability to translate technical AI concepts for non-technical stakeholders. Nice to have : Contributions to AI research (published papers, patents) or open-source AI projects (e.g., TensorFlow Agents, AutoGen). Experience with DevOps/MLOps toolsKubeflow, MLflow, Docker, or Terraform. Expertise in NLP, computer vision, or graph-based AI systems. Familiarity with quantum computing or neuromorphic architectures for AI. Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority Ratings - (Strategic Workforce Planning)

Job Summary Greetings from Sight Spectrum Technologies!!! We would like to ensure that you are interested in this position. Experience :5+Years Location: Chennai, Bangalore, Hyderabad, Coimbatore Description: Strong experience in ETL development, data modeling, and managing data in large-scale environments. Proficient in AWS services including SageMaker, S3, Glue, Lambda, and CloudFormation/Terraform. - Hands-on expertise withMLOpsbest practices, including model versioning, monitoring, and CI/CD for ML pipelines. Proficiency in Python and SQL; experience with Java is a plus for streaming jobs. Deep understanding of cloud infrastructure automation using Terraform or similar IaC tools. Excellent problem-solving skills with the ability to troubleshoot data processing and deployment issues. Experience in fast-paced, agile development environments with frequent delivery cycles.- Strong communication and collaboration skills to work effectively across cross-functional teams

Description : Strong experience in ETL development, data modeling, and managing data in large-scale environments. - Proficient in AWS services including SageMaker, S3, Glue, Lambda, and CloudFormation/Terraform. - Hands-on expertise with MLOps best practices, including model versioning, monitoring, and CI/CD for ML pipelines. - Proficiency in Python and SQL; experience with Java is a plus for streaming jobs. - Deep understanding of cloud infrastructure automation using Terraform or similar IaC tools. - Excellent problem-solving skills with the ability to troubleshoot data processing and deployment issues. - Experience in fast-paced, agile development environments with frequent delivery cycles. - Strong communication and collaboration skills to work effectively across cross-functional team Role & responsibilities

Key Responsibility: End-to-End Model Development Design, train, and deploy machine learning models (supervised/unsupervised learning, NLP, time-series forecasting) using Python (scikit-learn, TensorFlow, PyTorch) and R for specialized statistical analysis. Optimize models for computational efficiency via parallelization, quantization, and cloud-native architectures (AWS SageMaker, GCP Vertex AI). Data Engineering & Pipeline Automation Build robust ETL/ELT pipelines for structured/unstructured data using SQL, Spark, and Apache Airflow. Implement feature engineering workflows and ensure data quality for large-scale datasets (1M+ records). Cross-Functional Collaboration Partner with product, risk, and engineering teams to operationalize models into business applications (e.g., credit risk systems, customer segmentation tools). Mentor junior engineers and lead code reviews to maintain best practices in MLops workflows. Model Governance & Compliance Develop monitoring frameworks for model drift, bias detection, and performance degradation. Ensure compliance with regulatory standards and internal governance policies. Innovation & Research Stay ahead of industry trends (e.g., LLMs, generative AI) and prototype solutions using no-code platforms. Publish internal white papers on novel methodologies and present findings to stakeholders. Technical Requirements Core Skills: Python (expert), R (intermediate), SQL, Apache Spark, Apache Arrow, Pydantic Machine Learning: Regression, classification, clustering, deep learning (CNNs, RNNs) Frameworks: scikit-learn, PyTorch, TensorFlow, Hugging Face, MLflow Cloud: AWS/GCP/Azure or any cloud platform, Docker, Kubernetes Domain Expertise (Preferred): Financial services (PD/LGD modelling, ECL calculations, risk analytics) Experience with no-code platforms is a bonus Knowledge of regulatory frameworks (Basel III, IFRS 9) Soft Skills & Culture Fit Ownership Mindset: Take end-to-end responsibility for projects, from ideation to deployment. Collaboration: Excel in cross-functional teams with clear communication to technical and non-technical stakeholders. Innovation: Continuously explore emerging tools (e.g., LLMs, AutoML) to solve business challenges.

Must have: 5+ years of experience in designing, developing, and deploying AI/ML solutions, with at least 3+ years focused on AWS AI/ML services. Deep hands-on experience with Amazon SageMaker for building, training, tuning, and deploying ML models. Proven ability to work with AWS data services, such as: Amazon S3 (data storage),AWS Glue or AWS Data Wrangler (data processing), Amazon Athena or Redshift (querying/analytics) Familiarity with AWS AI services, like:Amazon Rekognition (computer vision), Amazon Comprehend (NLP), Amazon Transcribe/Polly (speech), Amazon Lex (chatbots) Experience building end-to-end ML pipelines using AWS-native tools or integrating with tools like Step Functions, Lambda, and CloudWatch for automation and monitoring. Solid understanding of model versioning, deployment strategies (real-time, batch, A/B testing), and model monitoring on AWS. Proficiency in Python for ML model development and deployment. Good to have: Hands-on experience with MLOps practices using AWS tools (e.g., SageMaker Pipelines, Model Registry, CodePipeline, CloudFormation). Familiarity with data lake architecture and tools like AWS Lake Formation. AWS certifications (e.g., AWS Certified Machine Learning Specialty, Solutions Architect – Associate/Professional).Experience with Application performance tuning

Strong understating of Python, ML concepts and frameworks, Fast API, Graph QL Experience in developing scalable APIs. Knowledge of AWS, preferred services are storage, EC2, Kubernetes Exposure of ML best practices, documentation and unit testing. ML Flow, AirFlow, ML pipeline creation, drift monitoring and control Experience in developing and deploying machine learning models in a production environment using CI/CD. Communicate with clients to understand requirements and ask right questions. Knowledge of Django and database design will be added advantage. Strong analytical and problem-solving skills. Standards : Model Deployment Standards Use standardized APIs (e.g., RESTful) to interface with models Implement model versioning and proper naming conventions Monitoring and Maintenance Schedule routine model retraining and monitoring Code Quality Standards Follow style guides (e.g., PEP 8 in Python) Write comprehensive debugging and tests

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Google Cloud Machine Learning Services Good to have skills : NA Minimum 5+ year(s) of experience is required Educational Qualification : BE Summary: As an AI/ML Engineer, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying GenAI models, developing cloud or on-prem application pipelines, and ensuring production-ready quality. You will also work with deep learning, neural networks, chatbots, and image processing. Key Responsibilities : A: Demonstrate various Google specific Designs using effective POCs, as per client requirements. B: Identifying applicability of Google Cloud AI services to use cases with ability to project both the business and tech benefits. C: Design, build and productionizes ML models to solve business challenges using Google Cloud technologies D: Lead and guide team of data scientists E: Coordinating and collaborating with cross-functional teams Technical Experience : A: Min 3 + years of experience on GCP AWS ML B: Exposure to Google Gen AI Services C: Exposure to GCP and its Compute, Storage, Data, Network, Security services D: Expert programming skills in any one of Java, Python, Spark E: Knowledge of GKE, Kubeflow on GCP would be good to have G: Experience in Vertex AI for building and managing the ML models H: Experience in implementing MLOps Additional Information: - The candidate should have a minimum of 5 +years of experience in Google Cloud Machine Learning Services.

Job Summary: We are seeking a visionary and hands-on AI Architect with 8+ years of experience in designing and deploying AI-driven systems, including Generative AI (GenAI), LLM integration, computer vision, and agentic workflows. This role demands deep technical expertise in transformer models, PyTorch, and tools such as Stable Diffusion, ControlNet, and LangChain, as well as a strong grasp of dataset strategy, bias mitigation, and scalable AI system architecture. Experience with e-commerce or fashion datasets is a strong plus. Key Responsibilities: Architect and lead the development of AI/ML systems, with a focus on Generative AI, including diffusion models, GANs, and LLMs. Implement and optimize models such as Stable Diffusion, ControlNet, and OpenPose for real-world use cases in visual content generation. Design LLM-integrated solutions using LangChain, agentic workflows, and multimodal AI systems. Collaborate with cross-functional teams to define dataset strategy, ensuring data relevance, diversity, and quality. Integrate Hugging Face Transformers and PyTorch-based architectures into production environments. Define and implement best practices around bias & fairness, model explainability, and ethical AI design. Lead architectural decisions for scalable AI platforms, focusing on performance, reliability, and continuous learning capabilities. Leverage domain knowledge in e-commerce/fashion for visual understanding, recommendation, or personalization solutions. Qualifications: 8+ years of experience in AI/ML system architecture, including 3+ years specifically in Generative AI and LLM ecosystems. Proficiency in PyTorch, Transformers, Hugging Face, and LangChain. Deep understanding of diffusion models, GANs, ControlNet, and OpenPose. Experience in designing agentic AI workflows, real-time inference systems, and production-grade AI infrastructure. Proven track record in dataset creation/curation, bias analysis, and fairness optimization. Strong communication skills and the ability to translate complex AI concepts into business impact. Preferred Qualifications : Prior experience with e-commerce, fashion technology, or retail-based AI datasets. Contributions to open-source AI frameworks or publications in relevant research areas. Familiarity with cloud AI services (e.g., AWS Sagemaker, Azure AI, or GCP Vertex AI). Understanding of AI observability, versioning, and model governance. Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI/ML Engineer, you will develop applications and systems utilizing AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production-ready quality. You will apply GenAI models as part of the solution, including deep learning, neural networks, chatbots, and image processing. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Lead the implementation of AI/ML models.- Conduct research on emerging AI technologies.- Optimize AI algorithms for performance and scalability. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Strong understanding of natural language processing techniques.- Experience with cloud AI services like AWS SageMaker or Google AI Platform.- Knowledge of deep learning frameworks such as TensorFlow or PyTorch.- Hands-on experience in developing AI applications.- Familiarity with deploying AI models in production environments. Additional Information:- The candidate should have a minimum of 12 years of experience in Large Language Models.- This position is based at our Hyderabad office.- A 15 years full-time education is required. Qualification 15 years full time education

Job Title: Industry & Function AI Decision Science Manager + S&C GN Management Level:07 - Manager Location: Primary Bengaluru, Secondary Gurugram Must-Have Skills: Consumer Goods & Services domain expertise , AI & ML, Proficiency in Python, R, PySpark, SQL , Experience in cloud platforms (Azure, AWS, GCP) , Expertise in Revenue Growth Management, Pricing Analytics, Promotion Analytics, PPA/Portfolio Optimization, Trade Investment Optimization. Good-to-Have Skills: Experience with Large Language Models (LLMs) like ChatGPT, Llama 2, or Claude 2 , Familiarity with optimization methods, advanced visualization tools (Power BI, Tableau), and Time Series Forecasting Job Summary : As a Decision Science Manager , you will lead the design and delivery of AI solutions in the Consumer Goods & Services domain. This role involves working closely with clients to provide advanced analytics and AI-driven strategies that deliver measurable business outcomes. Your expertise in analytics, problem-solving, and team leadership will help drive innovation and value for the organization. Roles & Responsibilities: Analyze extensive datasets and derive actionable insights for Consumer Goods data sources (e.g., Nielsen, IRI, EPOS, TPM). Evaluate AI and analytics maturity in the Consumer Goods sector and develop data-driven solutions. Design and implement AI-based strategies to deliver significant client benefits. Employ structured problem-solving methodologies to address complex business challenges. Lead data science initiatives, mentor team members, and contribute to thought leadership. Foster strong client relationships and act as a key liaison for project delivery. Build and deploy advanced analytics solutions using Accentures platforms and tools. Apply technical proficiency in Python, Pyspark, R, SQL, and cloud technologies for solution deployment. Develop compelling data-driven narratives for stakeholder engagement. Collaborate with internal teams to innovate, drive sales, and build new capabilities. Drive insights in critical Consumer Goods domains such as Revenue Growth Management Pricing Analytics and Pricing Optimization Promotion Analytics and Promotion Optimization SKU Rationalization/ Portfolio Optimization Price Pack Architecture Decomposition Models Time Series Forecasting Professional & Technical Skills: Proficiency in AI and analytics solutions (descriptive, diagnostic, predictive, prescriptive, generative). Expertise in delivering large scale projects/programs for Consumer Goods clients on Revenue Growth Management - Pricing Analytics, Promotion Analytics, Portfolio Optimization, etc. Deep and clear understanding of typical data sources used in RGM programs POS, Syndicated, Shipment, Finance, Promotion Calendar, etc. Strong programming skills in Python, R, PySpark, SQL, and experience with cloud platforms (Azure, AWS, GCP) and proficient in using services like Databricks and Sagemaker. Deep knowledge of traditional and advanced machine learning techniques, including deep learning. Experience with optimization techniques (linear, nonlinear, evolutionary methods). Familiarity with visualization tools like Power BI, Tableau. Experience with Large Language Models (LLMs) like ChatGPT, Llama 2. Certifications in Data Science or related fields. Additional Information: The ideal candidate has a strong educational background in data science and a proven track record in delivering impactful AI solutions in the Consumer Goods sector. This position offers opportunities to lead innovative projects and collaborate with global teams. Join Accenture to leverage cutting-edge technologies and deliver transformative business outcomes. About Our Company | AccentureQualification Experience: Minimum 7-9 years of experience in data science, particularly in the Consumer Goods sector Educational Qualification: Bachelors or Masters degree in Statistics, Economics, Mathematics, Computer Science, or MBA (Data Science specialization preferred)

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.