123 Unsupervised Learning Jobs

As a Generative AI Developer at our company, you will be responsible for building cutting-edge generative models to create innovative, human-like content across various domains such as natural language generation, image generation, and more. Your expertise in machine learning, deep learning, and natural language processing will be crucial for developing AI systems that utilize generative models like GPT, GANs, VAEs, and other neural networks. **Key Responsibilities:** - Develop and fine-tune generative models using techniques like GANs, VAEs, Transformers, and Diffusion models. - Work on tasks including text generation, image generation, music/sound generation, video creation, and other creative AI applications. - Design, build, and deploy models using frameworks like TensorFlow, PyTorch, Hugging Face, OpenAI's GPT, or similar tools. - Optimize AI models for performance, accuracy, and scalability in real-world production environments. - Research and stay updated on the latest trends, papers, and breakthroughs in generative AI. - Collaborate with other teams to integrate models into production systems. - Work on data preprocessing, augmentation, and designing pipelines to ensure high-quality input for model training. - Document your code, process, and model outputs for team-wide visibility and knowledge sharing. **Qualifications Required:** - Bachelor's or Master's degree in Computer Science or related fields. - 3-4 years of hands-on experience in developing Generative AI solutions. - Strong understanding of deep learning algorithms, especially in generative models like GANs, VAEs, Diffusion models, or large-scale language models like GPT. - Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face. - Experience working with neural networks, unsupervised learning, and NLP. - Strong programming skills in Python, including deep learning libraries. - Familiarity with cloud platforms (AWS, GCP, or Azure) for model training and deployment. - Strong mathematical and statistical knowledge, particularly in probability theory, linear algebra, and optimization. - Experience in large-scale model training, fine-tuning, or distributed computing. - Knowledge of reinforcement learning and self-supervised learning. - Familiarity with AI ethics, bias mitigation, and interpretability in generative models.,

National Payment Corporation of India (NPCI) is Hiring! Hiring Data Scientist (with Statistics, Quantitative Economics, Operations Research (OR), Bayesian Modelling experience only) Experience: 5 - 10 Years (Mandatory)Tier-1 schools/colleges: ISI, IITs (Kharagpur, Chennai, Kanpur and Bombay), BITS and DSE ( D elhi S chool of E conomics) or any similar Mandatory (Must) Must have experience of 5-10 years working in Statistics, Quantitative Economics, Operations Research (OR), Bayesian Modelling or any similar fields (Must) Atleast a Bachelors level education in Statistics, Economics, Industrial Engineering or any similar fields from Tier-1 schools/colleges Exposed to Supervised and Un-supervised Learning methods/algorithms from all genres viz. Statistical (e.g. Logistic, Discriminant, K-means etc), Machine Learning (e.g. Random Forest, SVM etc), or Deep Learning (e.g. NN, CNN etc) Excellent Python and SQL skills handling large volume of data have the flair to pick-up any language/technology/tool in quick time Passion in solving business problems with data Good storytelling and articulation skills Good teaming skills Proactive and can figure out things on his/her own attitude Should have good sense of ownership Ability to manage projects from conceptualization to presentation/delivery/adoption Good-to-have Some banking /finance background Worked with multiple business partners kind of scenario/environment Some stakeholder management skills External conference presentations / White Papers / Articles Publishing / Patents Some exposures using Google OR, IBM ILOG etc OR tools Some exposure to NLP ( N atural L anguage P rocessing)

As a Tech Lead specializing in Data & Analytics, you will be responsible for the following: **Role Overview:** You will play a crucial role in handling and processing data efficiently, ensuring optimal performance and data integrity. Additionally, you will be involved in data analysis, statistical modeling, and visualization to derive meaningful insights for the organization. **Key Responsibilities:** - Proficient in SQL Server with a focus on query optimization. - Expertise in application data design and process management. - Extensive knowledge of data modeling techniques. - Hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Microsoft Fabric. - Experience working with Azure Databricks. - Expertise in data warehouse development, including SSIS and SSAS. - Proficiency in ETL processes, data cleaning, and normalization. - Familiarity with big data technologies like Hadoop, Spark, and Kafka. - Understanding of data governance, compliance, and security within Azure environments. - Experience in data analysis, statistical modeling, and machine learning techniques. - Proficiency in analytical tools such as Python, R, and libraries like Pandas and NumPy. - Strong expertise in Power BI for data visualization, data modeling, and DAX queries. - Experience in implementing Row-Level Security in Power BI. - Ability to work with medium-complex data models and understand application data design quickly. - Familiar with industry best practices for Power BI and performance optimization. - Understanding of machine learning algorithms, including supervised, unsupervised, and deep learning techniques. **Qualifications Required:** - Ability to lead a team of 4-5 developers and take ownership of deliverables. - Commitment to continuous learning and staying updated with new technologies. - Strong communication skills in English, both written and verbal. - Effective interaction with customers during project implementation. - Capability to explain complex technical concepts to non-technical stakeholders. In addition to technical skills, the following skills are preferred for this role: - Data Management: SQL, Azure Synapse Analytics, Azure Analysis Service, Data Marts, Microsoft Fabric - ETL Tools: Azure Data Factory, Azure Databricks, Python, SSIS - Data Visualization: Power BI, DAX This comprehensive role requires a blend of technical expertise, leadership skills, and effective communication to drive successful data and analytics projects within the organization.,

You will be responsible for utilizing advanced analytics, machine learning, and statistical modeling techniques to help the retail business make data-driven decisions. You will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. **Key Responsibilities:** - Utilize your deep understanding of the retail industry to design AI solutions that address critical retail business needs. - Gather and clean data from various retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms like classification, clustering, regression, and deep learning to enhance predictive models. - Use AI-driven techniques for personalization, demand forecasting, and fraud detection. - Utilize advanced statistical methods to optimize existing use cases and build new products. - Stay updated on the latest trends in data science and retail technology. - Collaborate with executives, product managers, and marketing teams to translate insights into business actions. **Qualifications Required:** - Strong analytical and statistical skills. - Expertise in machine learning and AI. - Experience with retail-specific datasets and KPIs. - Proficiency in data visualization and reporting tools. - Ability to work with large datasets and complex data structures. - Strong communication skills to interact with both technical and non-technical stakeholders. - A solid understanding of the retail business and consumer behavior. - Programming Languages: Python, R, SQL, Scala - Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras - Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn - Big Data Technologies: Hadoop, Spark, AWS, Google Cloud - Databases: SQL, NoSQL (MongoDB, Cassandra) You will need a minimum of 3 years of experience and a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field to qualify for this position.,

Role & responsibilities : 1.Design and implement anomaly detection models using statistical and unsupervised learning techniques. 2.Optimize AI models for edge devices. 3.Work with time-series and sensor data, applying appropriate preprocessing, noise reduction, and feature extraction techniques. 4.Utilize deep learning architecture such as CNNs, RNNs, LSTM, GRU, and GANs. 5.Perform model evaluation, optimization, cross-validation, and hyperparameter tuning. 6.Visualize and analyze datasets using Python tools like Pandas, Matplotlib, and Seaborn. 7.Collaborate with cross-functional teams to translate business needs into AI-powered solutions. Good to have: 1.Sensor data processing (noise reduction, feature extraction, preprocessing techniques). 2.Gen AI and applying RAG technique would be added value. Interested candidate kindly share me your updated CV at jeeva@bvrpc.com

Role Overview: As a Senior Manager for data science, data modeling, and Analytics, you will lead a team of data scientists and analysts while actively contributing to the development and implementation of advanced analytics solutions. This role requires a blend of strategic leadership and hands-on technical expertise to drive data-driven decision-making across the organization. Key Responsibilities: - Design, develop, and deploy advanced machine learning models and statistical analyses to solve complex business problems. - Utilize programming languages such as Python, R, and SQL to manipulate data and build predictive models. - Understand end-to-end data pipelines, including data collection, cleaning, transformation, and visualization. - Collaborate with IT and data engineering teams to integrate analytics solutions into production environments. - Provide thought leadership on solutions and metrics based on the understanding of the nature of business requirements. Team Leadership & Development: - Lead, mentor, and manage a team of data scientists and analysts, fostering a collaborative and innovative environment. - Provide guidance on career development, performance evaluations, and skill enhancement. - Promote continuous learning and adoption of best practices in data science methodologies. - Engage and manage a hierarchical team while fostering a culture of collaboration. Strategic Planning & Execution: - Collaborate with senior leadership to define the data science strategy aligned with business objectives. - Identify and prioritize high-impact analytics projects that drive business value. - Ensure the timely delivery of analytics solutions, balancing quality, scope, and resource constraints. Client Engagement & Stakeholder Management: - Serve as the primary point of contact for clients, understanding their business challenges and translating them into data science solutions. - Lead client presentations, workshops, and discussions to communicate complex analytical concepts in an accessible manner. - Develop and maintain strong relationships with key client stakeholders, ensuring satisfaction and identifying opportunities for further collaboration. - Manage client expectations, timelines, and deliverables, ensuring alignment with business objectives. - Develop and deliver regular reports and dashboards to senior management, market stakeholders, and clients highlighting key insights and performance metrics. - Act as a liaison between technical teams and business units to align analytics initiatives with organizational goals. Cross-Functional Collaboration: - Work closely with cross-capability teams such as Business Intelligence, Market Analytics, Data Engineering to integrate analytics solutions into business processes. - Translate complex data insights into actionable recommendations for non-technical stakeholders. - Facilitate workshops and presentations to promote data-driven conversations across the organization. - Closely work with support functions to provide timely updates to leadership on operational metrics. Governance & Compliance: - Ensure adherence to data governance policies, including data privacy regulations (e.g., GDPR, PDPA). - Implement best practices for data quality, security, and ethical use of analytics. - Stay informed about industry trends and regulatory changes impacting data analytics. Qualifications: - Education: Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. - Experience: 12+ years of experience in advanced analytics, data science, data modeling, machine learning, Generative AI, or a related field with 5+ years in a leadership capacity. - Proven track record of managing and delivering complex analytics projects. - Familiarity with the BFSI/Hi Tech/Retail/Healthcare industry and experience with product, transaction, and customer-level data. - Experience with media data will be advantageous. Technical Skills: - Proficiency in programming languages like Python, R, or SQL. - Experience with data visualization tools (e.g., Tableau, Power BI). - Familiarity with big data platforms (e.g., Hadoop, Spark) and cloud services (e.g., AWS, GCP, Azure). - Knowledge of machine learning frameworks and libraries. Soft Skills: - Strong analytical and problem-solving abilities. - Excellent communication and interpersonal skills. - Ability to influence and drive change within the organization. - Strategic thinker with a focus on delivering business outcomes. Additional Company Details: The job is located in Bengaluru under the brand Merkle on a full-time permanent contract.,

Job Description: You will be responsible for leading the configuration, maintenance, and optimization of the organization's network and security infrastructure to ensure high performance and reliability. Your key responsibilities will include: - Architecting and integrating networks across multiple business units and diverse cloud environments, ensuring seamless connectivity and scalability. - Championing the use of Infrastructure as Code processes to automate and maintain infrastructure consistency, scalability, and up-to-date configurations. - Overseeing the configuration, deployment, and management of F5 Local Traffic Managers (LTMs) and Advanced Security Modules (ASMs) to ensure seamless application delivery and security. - Creating and implementing strategies for integrating cloud Virtual Private Clouds (VPCs), interconnects, and direct connects, ensuring efficient and secure data flow between on-premises and cloud environments. - Proactively identifying opportunities to enhance the network's scalability and resilience, ensuring it can handle growing business demands and traffic loads. - Working closely with infrastructure, application, and security teams to ensure network designs meet cross-functional requirements and adhere to best practices. Qualifications Required: - Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience. Company Details: Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do and they push us to ensure we take care of ourselves, each other, and our communities. If you want to learn more about our culture and community, you can visit https://about.pypl.com/who-we-are/default.aspx.,

As an AI/ML Engineer at our company, you will be part of a motivated team focusing on AI and Machine Learning projects. Your role involves working with Python programming and applying AI/ML fundamentals to design and deploy models effectively. **Key Responsibilities:** - Collaborate with senior engineers to design, implement, and deploy AI/ML models. - Write clean, efficient, and maintainable code in Python. - Assist in data pre-processing, feature engineering, and model evaluation. - Contribute to the development of algorithms and models for data extraction and analysis. - Stay updated with the latest advancements in AI/ML technologies and methodologies. **Qualifications Required:** - Bachelor's degree in Computer Science, Engineering, or a related field. - Strong proficiency in Python programming language. - Good understanding of AI/ML fundamentals, including supervised and unsupervised learning, neural networks, and model evaluation techniques. - Familiarity with popular AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Experience with data manipulation and analysis using libraries like pandas and NumPy. - Strong problem-solving skills and attention to detail. - Excellent written and verbal communication skills. If you have previous projects or coursework related to AI/ML, it would be considered an added advantage. Join us to kickstart your career in AI and Machine Learning by contributing to the development and deployment of cutting-edge AI/ML models.,

About The Role About The Role Template Job Title Manager Public Services - Data & AI Level : 09 Consultant Location Bengaluru / Gurugram /Mumbai Must have skills: Data & AI / GenAI Strategy development and deployment and large-scale transformation roadmaps for global public sector clients Experience in collaborating with Data & AI / GenAI teams for data fluency and delivering for product/solutions roadmap (including Data Scientists / AI Engineers / Responsible AI practitioners Designing and implementing public sector digital platforms and citizen experience solutions aligned with Data & AI / GenAI strategy of public sector clients Experience with Data & AI / GenAI Strategy design, solutions, benchmarking, best practices, and implementation Experience with key data providers (such as Snowflake, Databricks, AWS Sagemaker/Bedrock, GCP AI Platform/Vertex AI, and Azure) Experience with GenAI frameworks and approach for deployment and an understanding of model development, deployment, optimization, evaluation Experience with solutions involving Supervised / Unsupervised Learning, Deep Learning Applications, Reinforcement Learning, Model Interpretability, and Model Explainability Techniques Experience with solutions involving Content Generation, Language Translation and Localization, Chatbot Development, Text Summarization and Analysis, Multimodal Content Creation Good to have skills: Knowledge & experience in Public Sector verticals including Social Services, Healthcare, Education, Postal Services, Revenue, Border, Defense or related sectors in the Private Sector Creation of Strategic Vision & Roadmap, Data Readiness & Maturity Assessments, Value Assessments, Use-Case Prioritization plans, Ethics/Policy/Governance POVs, Targeting Operating Model & Design, Blueprinting & Solution Architecture, Change Management & Training Plans, Costing for AI deployment & model training/applications Policy formulation and regulatory compliance for Data & AI / GenAI. Job Summary : The Accenture Public Services Strategy team is seeking a highly skilled and innovative Public Sector Strategy Manager. This role is pivotal in driving the Data & AI / GenAI agenda, enhancing data infrastructure, and developing Data & AI / GenAI solutions to improve public services. The ideal candidate will have a background in digital government initiatives with a sectoral/functional focus, and a passion for public service. Roles & Responsibilities: Public Sector Data & AI / Gen AI Strategy Develop and implement a comprehensive Data & AI / GenAI strategy aligned with governmental objectives and public sector needs. Designing and implementing Data Platforms / AI Platforms, personalization frameworks and customer experience solutions Identify and leverage emerging Data & AI / GenAI technologies to enhance digital service delivery and citizen engagement Conversant with product backlogs, user requirement gathering, developing user personas, service journey, wireframes, UI/UX etc.with a sector/functional focus Promote Data & AI / GenAI literacy and culture within the organization and across public services. Measure and report on the effectiveness of Data & AI / GenAI initiatives and suggest improvements. Professional & Technical Skills: Data & AI / GenAI Strategy Design and Implementation Digital Product Strategy Data & AI / GenAI Solutions Data & AI / GenAI Frameworks for deployment Data & AI / GenAI Benchmarking, best practices, and implementation Operating Model Design Creation of Strategic Vision & Roadmap Data Readiness & Maturity Assessments Value Assessments Use-Case Prioritization plans Targeting Operating Model & Design Blueprinting & Solution Architecture Change Management & Training Plans Cost Analysis for AI deployment & model training/applications About Our Company | Accenture Qualification Experience: Minimum 3-6 year(s) of experience is required Educational Qualification: Bachelors degree in information technology, computer science, or a related field. MBA or a postgraduate degree from a Tier 1 B-School with rich experience in building Data & AI / GenAI strategy and working with public sector clients.

The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help the retail business make data-driven decisions. This individual will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Key Responsibilities: - Utilize deep understanding of the retail industry to design AI solutions for critical business needs. - Gather and clean data from various retail sources like sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. - Apply machine learning algorithms for classification, clustering, regression, and deep learning to enhance predictive models. - Utilize AI-driven techniques for personalization, demand forecasting, and fraud detection. - Implement advanced statistical methods to optimize existing use cases and develop new products. - Stay informed about the latest trends in data science and retail technology. - Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional Skills: - Strong analytical and statistical skills. - Expertise in machine learning and AI. - Experience with retail-specific datasets and KPIs. - Proficiency in data visualization and reporting tools. - Ability to work with large datasets and complex data structures. - Strong communication skills for interaction with technical and non-technical stakeholders. - Solid understanding of the retail business and consumer behavior. Technical Skills: - Programming Languages: Python, R, SQL, Scala - Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow, Keras - Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn - Big Data Technologies: Hadoop, Spark, AWS, Google Cloud - Databases: SQL, NoSQL (MongoDB, Cassandra) Minimum Qualifications: - Experience: Minimum 3 years of relevant experience. - Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. Location: Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must-Have Skills: - Solid understanding of retail industry dynamics and key performance indicators. - Ability to communicate complex data insights to non-technical stakeholders. - Meticulous in ensuring data quality and consistency. - Proficiency in Python for data manipulation, statistical analysis, and machine learning. - Experience with supervised and unsupervised learning algorithms. - Use advanced analytics to optimize pricing strategies based on market demand. Good-to-Have Skills: - Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms. - Experience with ETL processes and tools like Apache Airflow. - Familiarity with designing scalable and efficient data pipelines and architecture. - Experience with data visualization tools like Tableau, Power BI, Matplotlib, and Seaborn.,

About the Team The Panacea team has a passionate set of engineers across India and US office. We move fast, collaborate closely, and care deeply about quality and ownership. Our mission is to deliver AI/ML-powered developer productivity tools that solve real engineering and support pain points at scale. Why Join Us Build AI-first observability tools that redefine how engineers triage and troubleshoot. Own systems that reduce hours of manual work in engineering and SRE workflows . Collaborate with a tight-knit team of high-ownership engineers who are passionate about impact and innovation. Hybrid work model that supports flexibility and deep focus. Help shape the central AI charter at Nutanix and influence future AI products across the company. Your Role AI-Powered Observability Platform : Own the vision, architecture, and delivery of Panaceas ML-based log and metrics analyzer that reduces triage time and improves engineering efficiency. AI/ML-powered Log Analyzer Tool : Use deep learning (e.g., ModernBERT ) to represent log messages, detect anomalies, group patterns, and surface actionable insights to users. Metrics Anomaly Detection Engine : Build robust ML models to detect anomalies in time-series metrics like CPU, memory, disk I/O, network traffic, service health , and moreautomatically identifying performance degradation or system regressions across distributed environments. Auto-RCA Engine : Combine log and metrics signals with graph-based correlation and LLM-powered summarization to automatically diagnose the root cause of system failures. Feedback Loop & Continuous Learning : Build infrastructure for incorporating user feedback to continuously retrain and improve anomaly detection systems. LLM Integration : Integrate LLMs for user queries, problem summarization, anomaly explanation, and contextual recommendations. Central AI Charter : Contribute to Nutanixs foundational AI platform by defining shared tooling, datasets, governance, and reusable ML components across products. Responsibilities Architect and scale ML pipelines for real-time and batch-based anomaly detection in both logs and time-series metrics. Build and fine-tune ModernBERT and other transformer-based models for log understanding, anomaly classification, and summarization. Develop unsupervised and semi-supervised ML models for detecting anomalies in system metrics (CPU, memory, network throughput, latency, etc.). Implement correlation models to connect anomalies across logs and metrics to form a cohesive RCA narrative. Own the entire ML lifecycle: data ingestion, feature extraction, model training, evaluation, deployment, and monitoring. Build explainable AI systems that increase adoption and trust within engineering, QA, and support teams. Collaborate with cross-functional stakeholders (SRE, QA, Dev) to deeply understand pain points and translate them into intelligent tooling. Drive technical excellence through code and design reviews, mentoring, and setting engineering best practices. What You Will Bring Educational Background : B.Tech/M.Tech in Computer Science, Machine Learning, AI, or related fields. Experience : 12+ years of engineering experience , including designing , developing and deploying AI/ML systems at scale. ML Expertise : Strong in time-series anomaly detection, statistical modeling, supervised/unsupervised learning. Experience building ML models for metrics data (CPU, memory, IOPS, network, etc.) using models like Isolation Forest, Prophet, LSTM, or deep autoencoders. Expertise in NLP using ModernBERT, BERT, or log classification, clustering, and summarization. Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A. Engineering Skills : Strong Python background, hands-on with ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Familiar with data pipelines and serving models. Observability Knowledge : Hands-on with logs, metrics, traces, and popular monitoring tools (e.g., Prometheus, Grafana, ELK). Leadership : Ability to independently drive projects from requirements to delivery, mentor junior engineers, and deliver business impact.

About The Role Skill required: Delivery - Advanced Analytics Designation: I&F Decision Science Practitioner Specialist Qualifications: Master of Engineering,Masters in Business Economics Years of Experience: 7 to 11 Years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do? Data & AI. You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for? Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domainsEnergy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. QualificationsMasters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Leading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Qualification Master of Engineering,Masters in Business Economics

About The Role Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Assoc Mgr Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 10 to 14 years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do? Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for? Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains:Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. Qualifications:Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Leading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Qualification Master of Engineering,Masters in Business Economics

About The Role Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 7 to 11 years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do? Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for? Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains:Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. Qualifications:Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Building data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Utilizing advanced statistical and machine learning techniques to develop models that can assist in decision-making and strategic planning. Refining and improving data science models based on feedback, new data, and evolving business needs. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Qualification Master of Engineering,Masters in Business Economics

About The Role Skill required: Data Scientist - Data Science Designation: I&F Decision Science Practitioner Specialist Qualifications: Any Graduation Years of Experience: Experienced About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do? You will be aligned with our Insights & Intelligence vertical and help us generate insights by leveraging the latest Artificial Intelligence (AI) and Analytics techniques to deliver value to our clients. You will also help us apply your expertise in building world-class solutions, conquering business problems, addressing technical challenges using AI Platforms and technologies. You will be required to utilize the existing frameworks, standards, patterns to create architectural foundation and services necessary for AI applications that scale from multi-user to enterprise-class and demonstrate yourself as an expert by actively blogging, publishing research papers, and creating awareness in this emerging area. You will be working as a part of Marketing & Customer Analytics team which provides a set of processes that measure, manage and analyze marketing activities in order to provide actionable insights and recommendations to marketing organizations in terms of optimizing ROI & performance efficiency in operations.Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. You should have exposure to digital marketing, A/B testing, MVT, Google Analytics/Site Catalyst. You will be a core member of Accenture Operations global Applied Intelligence group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. The objectives of the team include but are not limited toLeading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. What are we looking for? Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience - Python, R, SAS, S-plus, MATLAB, STATA or SPSS. Experience working with large data sets and big data tools like Snowflake, AWS, Spark, etc. Solid knowledge in at least one of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc.), Multivariate Statistics, Non-parametric Methods, Reliability Models, Markov Models, Stochastic models, Bayesian Models Experience in atleast one of these business domainsCPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Roles and Responsibilities: In this role you are required to do analysis and solving of moderately complex problems Typically creates new solutions, leveraging and, where needed, adapting existing methods and procedures The person requires understanding of the strategic direction set by senior management as it relates to team goals Primary upward interaction is with direct supervisor or team leads Generally, interacts with peers and/or management levels at a client and/or within Accenture The person should require minimal guidance when determining methods and procedures on new assignments Decisions often impact the team in which they reside and occasionally impact other teams Individual would manage medium-small sized teams and/or work efforts (if in an individual contributor role) at a client or within Accenture Please note that this role may require you to work in rotational shifts Qualification Any Graduation

About The Role Skill required: Data Scientist - Data Science Designation: Analytics Associate Manager - Insights and Intelligence Qualifications: Any Graduation Years of Experience: Experienced About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do? You will be aligned with our Insights& Intelligence vertical and help us generate insights by leveraging the latest Artificial Intelligence (AI) and Analytics techniques to deliver value to our clients. You will also help us apply your expertise in building world-class solutions, conquering business problems, addressing technical challenges using AI Platforms and technologies. You will be required to utilize the existing frameworks, standards, patterns to create architectural foundation and services necessary for AI applications that scale from multi-user to enterprise-class and demonstrate yourself as an expert by actively blogging, publishing research papers, and creating awareness in this emerging area. You will be working as a part of Marketing & Customer Analytics team which provides a set of processes that measure, manage and analyze marketing activities in order to provide actionable insights and recommendations to marketing organizations in terms of optimizing ROI & performance efficiency in operations.Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. You should have exposure to digital marketing, A/B testing, MVT, Google Analytics/Site Catalyst. You will be a core member of Accenture Operations global Applied Intelligence group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. The objectives of the team include but are not limited toLeading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. What are we looking for? Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience - Python, R, SAS, S-plus, MATLAB, STATA or SPSS. Experience working with large data sets and big data tools like Snowflake, AWS, Spark, etc. Solid knowledge in at least one of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc.), Multivariate Statistics, Non-parametric Methods, Reliability Models, Markov Models, Stochastic models, Bayesian Models Experience in atleast one of these business domainsCPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Roles and Responsibilities In this role you are required to do analysis and solving of moderately complex problems Typically creates new solutions, leveraging and, where needed, adapting existing methods and procedures The person requires understanding of the strategic direction set by senior management as it relates to team goals Primary upward interaction is with direct supervisor or team leads Generally, interacts with peers and/or management levels at a client and/or within Accenture The person should require minimal guidance when determining methods and procedures on new assignments Decisions often impact the team in which they reside and occasionally impact other teams Individual would manage medium-small sized teams and/or work efforts (if in an individual contributor role) at a client or within Accenture Please note that this role may require you to work in rotational shifts Roles and Responsibilities: In this role you are required to do analysis and solving of moderately complex problems Typically creates new solutions, leveraging and, where needed, adapting existing methods and procedures The person requires understanding of the strategic direction set by senior management as it relates to team goals Primary upward interaction is with direct supervisor or team leads Generally, interacts with peers and/or management levels at a client and/or within Accenture The person should require minimal guidance when determining methods and procedures on new assignments Decisions often impact the team in which they reside and occasionally impact other teams Individual would manage medium-small sized teams and/or work efforts (if in an individual contributor role) at a client or within Accenture Please note that this role may require you to work in rotational shifts Qualification Any Graduation

As a highly skilled individual in the field of AI and machine learning, you will be responsible for designing and implementing advanced machine learning models and deep learning algorithms. Your expertise will be utilized to develop scalable ML pipelines using tools such as TensorFlow, PyTorch, Scikit-learn, or similar platforms. You will take the lead in managing the end-to-end model lifecycle, starting from data preparation to deployment and monitoring. Collaboration will be a key aspect of your role, as you will work closely with data engineers, software developers, and domain experts to seamlessly integrate AI/ML solutions into various products. Your responsibilities will also include model tuning, evaluation, and optimization to ensure accuracy and performance meet the desired standards. Additionally, creating technical documentation and presenting your findings to stakeholders will be crucial in this position. To excel in this role, you must hold a Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or a related field. A Ph.D. would be preferred. Your extensive experience of 10+ years in software engineering or data science, with a minimum of 5+ years focused on AI/ML development, will be invaluable. You should have hands-on expertise in supervised/unsupervised learning, NLP, computer vision, recommendation systems, deep learning frameworks (such as TensorFlow, PyTorch), and model deployment tools like Docker, Flask, FastAPI, Kubernetes, etc. Proficiency in Python and its data ecosystem (Pandas, NumPy, Scikit-learn) is essential for this role. Moreover, strong knowledge of cloud platforms (AWS, GCP, Azure) for model deployment is required. Exceptional problem-solving and communication skills will further enhance your performance in this position. It would be advantageous if you have experience with large language models (LLMs), transformers, generative AI, and familiarity with MLOps tools (MLflow, Kubeflow, Vertex AI). Prior involvement in remote or contract roles, along with contributions to open-source AI/ML projects or research paper publications, would be considered a plus. This is a full-time role with contractual/temporary or freelance opportunities available, with a contract length of 12 months. The work schedule is during the day shift, and the work location is in person. Thank you for considering this exciting opportunity to leverage your AI/ML expertise and drive innovation in a dynamic work environment.,

We are seeking an experienced Data Architect to become a valuable member of our diverse team. In this role, your primary focus will be on delivering top-notch, scalable solutions by utilizing your expertise in Gen AI solutions, cloud technologies, and system design to exceed customer expectations. Your responsibilities will include designing and developing architectural concepts, creating technical roadmaps, and ensuring that software architecture aligns with business requirements. You will be responsible for setting up Continuous Integration, analyzing large databases on scalable cloud infrastructures, and developing prototypes using big-data technologies. As a Data Architect, you will also be expected to demonstrate cloud expertise by developing and deploying applications on leading cloud platforms, providing technical leadership, coaching team members on software design approaches, and leading efforts in application integration with PLM systems like SAP. To qualify for this role, you should hold a BE / B. Tech / ME / M. Tech degree with a minimum of 8 years of experience in data projects, including at least 2 years as a Data Architect. Your desired knowledge and experience should include a strong understanding of Data Pipelines, DevOps, Data Analysis, Data Modeling, Data Warehouse Design, Data Integration patterns, and various data management technologies. Additionally, you should possess expertise in technologies such as Python/JAVA, NO SQL DB, ETL and DWH concepts, SQL, Azure DevOps, Docker, Kubernetes, REST API, and have hands-on experience in Azure Cloud services. Knowledge of Machine Learning & Deep Learning, fine-tuning pre-trained models, model deployment, API development & integration, and event-driven architecture will be advantageous. Soft skills and other capabilities required for this role include excellent problem-solving and decision-making skills, effective communication abilities, the capacity to work independently, self-motivation, and strong teamwork skills to lead and motivate team members technically.,

S&C Global Network - AI - Retail - Consultant - AI/Gen AI Retail Specialist Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: Strong understanding of retail industry Ability to work with large datasets from different sources (e.g., transactional data, customer data, social media data) and data preprocessing techniques. Expertise in supervised and unsupervised learning algorithms Proficiency in deep learning frameworks like TensorFlow or PyTorch Ability to implement NLP techniques for chatbots, recommendation systems, sentiment analysis, and personalized search. Good to have skills: Familiarity with SQL, NoSQL databases, and big data technologies like Spark for handling large-scale data. Familiarity with transformer-based models such as BERT, GPT, and T5 for understanding and generating human language. Experience with Generative Pre-trained Transformers (GPT) Experience with Data Visualization Tools Job Summary :As an AI/Gen AI Retail Specialist, you will play a crucial role in leveraging advanced machine learning, deep learning, and generative AI technologies to transform retail strategies, improve customer experiences, and optimize operations. Your expertise in AI will drive the development of cutting-edge solutions that enhance retail performance across various domains, including merchandising, pricing, customer engagement, and product assortment. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Design, develop, and implement AI algorithms (machine learning, deep learning, etc.) and generative models (e.g., GPT, GANs) tailored to the retail sector. Focus on the creation of AI models that can help in wide range of use cases across customer lifecycle, personalized customer experiences, optimize pricing, and product assortment. Analyze and preprocess large datasets from various sources (sales data, customer data, inventory data) to build effective AI models. Translate data insights into actionable strategies for marketing, merchandising, and customer experience teams. For example, identifying cross-selling opportunities or optimizing product assortments. Provide regular reports and dashboards on AI model performance, business impact, and KPIs, communicating the results effectively to stakeholders. Work closely with cross-functional teams (e.g., product, marketing, business development) to understand the retail business challenges and translate them into AI-driven solutions. Communicate the potential of AI solutions to both technical and non-technical stakeholders, ensuring alignment between technical capabilities and business objectives. Professional & Technical Skills : Expertise in machine learning, natural language processing (NLP), and generative AI models. Experience with platforms like TensorFlow, PyTorch, and OpenAI technologies. Knowledge of AI ethics and responsible AI practices.

Job Title - Retail Specialized Data Scientist Level 9 SnC GN Data & AI Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: A solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Strong ability to communicate complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. Meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Strong proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). Expertise in supervised and unsupervised learning algorithms Use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. Good to have skills: Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL (Extract, Transform, Load) processes and tools like Apache Airflow to automate data workflows. Familiarity with designing scalable and efficient data pipelines and architecture. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly. Job Summary :The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help our retail business make data-driven decisions. This individual will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. Use AI-driven techniques for personalization, demand forecasting, and fraud detection. Use advanced statistical methods help optimize existing use cases and build new products to serve new challenges and use cases. Stay updated on the latest trends in data science and retail technology. Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional & Technical Skills : Strong analytical and statistical skills. Expertise in machine learning and AI. Experience with retail-specific datasets and KPIs. Proficiency in data visualization and reporting tools. Ability to work with large datasets and complex data structures. Strong communication skills to interact with both technical and non-technical stakeholders. A solid understanding of the retail business and consumer behavior. Programming Languages:Python, R, SQL, Scala Data Analysis Tools:Pandas, NumPy, Scikit-learn, TensorFlow, Keras Visualization Tools:Tableau, Power BI, Matplotlib, Seaborn Big Data Technologies:Hadoop, Spark, AWS, Google Cloud Databases:SQL, NoSQL (MongoDB, Cassandra)

Job Title - Retail Specialized Data Scientist Level 9 SnC GN Data & AI Management Level:09 - Consultant Location:Bangalore / Gurgaon / Mumbai / Chennai / Pune / Hyderabad / Kolkata Must have skills: A solid understanding of retail industry dynamics, including key performance indicators (KPIs) such as sales trends, customer segmentation, inventory turnover, and promotions. Strong ability to communicate complex data insights to non-technical stakeholders, including senior management, marketing, and operational teams. Meticulous in ensuring data quality, accuracy, and consistency when handling large, complex datasets. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Strong proficiency in Python for data manipulation, statistical analysis, and machine learning (libraries like Pandas, NumPy, Scikit-learn). Expertise in supervised and unsupervised learning algorithms Use advanced analytics to optimize pricing strategies based on market demand, competitor pricing, and customer price sensitivity. Good to have skills: Familiarity with big data processing platforms like Apache Spark, Hadoop, or cloud-based platforms such as AWS or Google Cloud for large-scale data processing. Experience with ETL (Extract, Transform, Load) processes and tools like Apache Airflow to automate data workflows. Familiarity with designing scalable and efficient data pipelines and architecture. Experience with tools like Tableau, Power BI, Matplotlib, and Seaborn to create meaningful visualizations that present data insights clearly. Job Summary : The Retail Specialized Data Scientist will play a pivotal role in utilizing advanced analytics, machine learning, and statistical modeling techniques to help our retail business make data-driven decisions. This individual will work closely with teams across marketing, product management, supply chain, and customer insights to drive business strategies and innovations. The ideal candidate should have experience in retail analytics and the ability to translate data into actionable insights. Roles & Responsibilities: Leverage Retail Knowledge:Utilize your deep understanding of the retail industry (merchandising, customer behavior, product lifecycle) to design AI solutions that address critical retail business needs. Gather and clean data from various retail sources, such as sales transactions, customer interactions, inventory management, website traffic, and marketing campaigns. Apply machine learning algorithms, such as classification, clustering, regression, and deep learning, to enhance predictive models. Use AI-driven techniques for personalization, demand forecasting, and fraud detection. Use advanced statistical methods help optimize existing use cases and build new products to serve new challenges and use cases. Stay updated on the latest trends in data science and retail technology. Collaborate with executives, product managers, and marketing teams to translate insights into business actions. Professional & Technical Skills : Strong analytical and statistical skills. Expertise in machine learning and AI. Experience with retail-specific datasets and KPIs. Proficiency in data visualization and reporting tools. Ability to work with large datasets and complex data structures. Strong communication skills to interact with both technical and non-technical stakeholders. A solid understanding of the retail business and consumer behavior. Programming Languages:Python, R, SQL, Scala Data Analysis Tools:Pandas, NumPy, Scikit-learn, TensorFlow, Keras Visualization Tools:Tableau, Power BI, Matplotlib, Seaborn Big Data Technologies:Hadoop, Spark, AWS, Google Cloud Databases:SQL, NoSQL (MongoDB, Cassandra) Additional Information: - Qualification Experience: Minimum 3 year(s) of experience is required Educational Qualification: Bachelors or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.

As an Associate Architect Machine Learning (ML) with 4-7 years of experience, you will play a crucial role in integrating generative AI (Gen AI) capabilities into various Software Development Lifecycle (SDLC) phases to enhance efficiency and innovation. Your primary focus will be on identifying high-impact business opportunities where Gen AI adoption can accelerate project delivery and improve solutioning across multiple domains. This position requires a blend of technical expertise, strategic thinking, and client engagement skills to successfully drive Gen AI implementation. Your responsibilities will include collaborating across multiple projects to identify Gen AI and ML strategies, leading discussions with clients to understand their pain points and recommend AI-driven solutions, actively contributing to strategy and operational meetings, and working closely with project engineering and product teams to implement Gen AI capabilities into production-ready solutions. You will also be involved in conducting proof-of-concepts (POCs) and feasibility studies, assisting teams with ML model selection, training, and deployment, and mentoring junior engineers and data scientists in best practices for ML and Gen AI development. To excel in this role, you must possess strong technical expertise in traditional ML techniques (supervised/unsupervised learning, time series forecasting, NLP) and Gen AI models (LLMs, diffusion models, transformers). Proficiency in Python, TensorFlow, PyTorch, and experience with cloud-based ML services (AWS, GCP, Azure) is essential. You should also be adept at architecting and optimizing scalable AI systems using microservices, containerization, and distributed computing for high availability and cost efficiency. Additionally, you must demonstrate strategic thinking skills by identifying and assessing new Gen AI opportunities in business processes, along with strong client handling and communication abilities to lead client discussions, presentations, and workshops effectively. Preferred qualifications for this role include prior experience in Gen AI solutioning for enterprise use cases, familiarity with LLM fine-tuning, prompt engineering, and knowledge retrieval techniques, as well as experience in deploying ML solutions in production environments at scale. Joining our team will provide you with the opportunity to be at the forefront of AI-driven innovation, collaborate with top AI/ML experts, and work on challenging projects that leverage cutting-edge AI technologies. If you are passionate about ML, Gen AI, and driving innovation, we invite you to apply and be a part of shaping the future of AI-driven solutions. Apply now to embark on this exciting journey with us.,

As a software engineer at Google, you will be part of a dynamic team that develops cutting-edge technologies to revolutionize how billions of users worldwide connect, explore, and interact with information. Our projects encompass a wide range of areas such as information retrieval, distributed computing, system design, networking, security, artificial intelligence, natural language processing, UI design, and mobile technologies. Your role will involve working on pivotal projects that address Google's evolving needs, with the flexibility to transition between teams and projects as both you and our business progress. Google Play is a platform that offers a variety of digital content, including music, movies, books, apps, and games. As a member of the Android and Mobile team focusing on Google Play, you will contribute to diverse aspects such as engineering backend systems, shaping product strategies, and establishing content partnerships. Your efforts will enable users to seamlessly access their purchased content across multiple devices through cloud synchronization. Responsibilities: - Apply expertise in Machine Learning to enhance user safety. - Integrate online/offline systems with various Google platforms to access signals, features, and insights. - Collaborate with subject matter experts to set up data pipelines for analysis and machine learning modeling. - Develop, code, and enhance automated review and detection models. - Lead projects in conjunction with other shopping horizontal teams, leveraging Machine Learning expertise to define projects, solutions, and oversee implementation. Minimum Qualifications: - Bachelor's degree or equivalent practical experience. - 5 years of software development experience in one or more programming languages, along with proficiency in data structures and algorithms. - 3 years of experience with Machine Learning/Artificial Intelligence algorithms and tools, or natural language processing. - 3 years of experience testing, maintaining, or launching software products. - 1 year of experience in software design and architecture. Preferred Qualifications: - Proficiency in C++ or Python. - Knowledge of machine learning concepts such as supervised and unsupervised learning, clustering, semi-supervised learning, anomaly detection, and Large Language Model (LLM) fine-tuning. - Familiarity with data analysis and Machine Learning frameworks. - Understanding of computer science principles and Google infrastructure, including databases, operating systems, algorithms, and Machine Learning technologies.,

You should possess a qualification of M.Tech / M.E / MS / M.Sc / Ph.D in Computer Science or a related discipline (Applied Mathematics, Statistics, Electrical and/or Computer Engineering) with a focus on Artificial Intelligence / Machine Learning. A CGPA of 7.5/10 or above in UG as well as PG level (in case of percentage, 70% or above) is required. You should have a minimum of 2 years of experience. As a team member, you will be responsible for applied research, development, and validation of advanced machine learning and AI algorithms for solving complex real-world problems at scale. Collaborating closely with the product team, you will analyze business problems and product vision to innovate algorithmic solutions. Your role will involve creating prototypes and demonstrations to validate innovative ideas and translating research outcomes into productized innovation by working with AI Engineers and software engineers. Additionally, you will create and maintain research plans, conduct experiments, consolidate and document results, and publish works as appropriate. It is important to document and protect intellectual property (IP) generated from R&D efforts by collaborating with designated teams and/or external agencies. Furthermore, mentoring junior staff to ensure correct procedures are followed, and collaborating with stakeholders, academic/research partners, and peer researchers to deliver tangible outcomes will be part of your responsibilities. The ideal candidate is expected to have a strong foundation in computer science fundamentals and analyzing and designing AI/Machine learning algorithms. Hands-on experience in at least two of the following areas is required: Supervised, unsupervised and semi-supervised machine learning algorithms, Reinforcement Learning, Deep learning & Representation Learning, Knowledge-based systems (knowledge representation, reasoning, and planning; FOL, ontologies etc.), Evolutionary Computing, Probabilistic Graphical Models, Streaming, incremental, and non-stationary learning. You should be proficient in at least one programming language and have experience in implementing AI/machine learning algorithms in Python or R. Additionally, experience with tools/frameworks/libraries such as Jupyter/Zeppelin, scikit-learn, matplotlib, pandas, Tensorflow, Keras, Apache Spark, etc. would be desirable. Applied research experience of at least 2-5 years on real-world problems using AI/Machine Learning techniques is necessary. Having at least one publication in a top-tier conference/journal related to AI/Machine Learning (E.g. ICML, AAAI, NIPS, ICCV, CVPR, KDD, SIGMOD, IJCNN, IJCAI, EMNLP, ICPR, ICDM, etc.) and/or patents would be beneficial. Experience in contributing to open-source projects related to AI/Machine Learning would be considered a strong advantage. This position is for Job Code: DSM_TVM and is located in Trivandrum. For further information, please reach out via email to recruitment@flytxt.com.,

You will be joining Dark Matter Technologies, a company leading the tech-driven revolution in loan origination with cutting-edge AI and origination technology solutions. As a Senior Data Scientist, your role will involve building machine learning models, using various algorithms for regression, prediction, and deep learning. You will be responsible for identifying data sources, analyzing data, writing machine code in Python (or Azure ML), and creating models. The job location is in Hyderabad and Bhubaneswar. Your responsibilities will include selecting features, building, and optimizing classifiers using machine learning techniques, conducting hypothesis testing, and developing predictive models. You will collaborate with cross-functional teams to integrate AI models into business solutions, conduct research to improve AI models and algorithms, and stay updated with the latest AI/ML technologies and trends. Additionally, you will implement and deploy AI models using cloud AI services while ensuring the quality and scalability of AI solutions. To qualify for this role, you should have at least 10 years of experience in Predictive Analytics and Data Mining, with hands-on experience in various areas such as linear regression, classification techniques, logistic regression, unsupervised learning techniques, feature reduction methods, and optimization methods. You must be proficient in working with R/Python, T-SQL, and graph-based models, with hands-on development experience in Python. Understanding of Azure Machine Learning and other Azure AI tools is essential, along with proficiency in data modeling, design, SQL development, and deploying machine learning models for key use cases. Preferred skills include exposure to machine learning libraries like Scikit-learn, TensorFlow, or PyTorch, leveraging Azure Machine Learning for managing data pipelines, experiments, and deployments, and implementing end-to-end AI solutions using Azure AI services. Certification in Microsoft Azure AI relative to Azure Machine Learning, expert database knowledge in SQL, and proficiency in Azure Data Services are also advantageous. You should possess strong problem-solving skills, the ability to work independently and as part of a team, excellent communication skills to convey complex technical concepts to non-technical stakeholders, and a solid understanding of statistical analysis and machine learning algorithms. Your role will involve working with large-scale datasets, ensuring efficiency and scalability in data processing, collaborating with stakeholders to design data science solutions, and presenting analytical findings and business insights to project managers and senior leadership. Keeping abreast of new statistical and machine learning techniques is crucial to improve predictive performance.,