34 Unsupervised Learning Jobs

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.

Title : S&C Global Network - AI - Retail - Consultant - AI/Gen AI Retail Specialist Job Title - AI/Gen AI Retail Specialist Level 9 SnC GN Data & AI 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. Additional Information: About Our Company | Accenture (do not remove the hyperlink) Qualification Experience: Minimum 3 year(s) of experience is required Educational Qualification: Msc. Statistics, B.Tech. / M.Tech Computer Science, Econometrics, Data Science

Skill required: Data Scientist - Data Science Designation: Specialist Qualifications: Any Graduation Years of Experience: 7 - 11 Years About Accenture 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. 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

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 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. Qualifications Master of Engineering,Masters in Business Economics

Skills: 3-8 of experience with Python for data analysis and modeling. Strong understanding of machine learning fundamentals , including supervised and unsupervised techniques. Hands-on experience with ML libraries such as scikit-learn , pandas , and NumPy . Comfortable working with real-world datasets, data cleaning, and preprocessing. Curious, analytical mindset with a passion for solving research and data challenges. Ability to break down problems, explore data patterns, and assist in delivering model-driven solutions. Exposure to working with unstructured or semi-structured data (text, PDFs, etc.) is a plus. Exposure to cloud platforms (AWS, GCP, Azure). Familiarity or experience with GenAI tools such as LangChain , LangGraph , or CrewAI . Understanding or hands-on experience with LLM-based projects .

We are seeking an experienced and hands-on Senior Data Scientist with expertise in Generative AI and/or Classical Machine Learning to join our growing AI team. In this role, you will lead the design and development of data-driven solutions , ranging from traditional ML models to cutting-edge GenAI applications that solve real business problems. Key Responsibilities: Develop, validate, and deploy ML models for prediction, classification, recommendation, and other business use cases. Design and build GenAI applications using LLMs (e.g., GPT, LLaMA, Claude) for use cases like summarization, Q&A, content generation, document analysis, etc. Collaborate with stakeholders to translate business problems into data science solutions . Perform EDA, feature engineering , and data preprocessing on structured and unstructured data (text, images, documents). Implement model performance monitoring , drift detection, and retraining strategies. Work with MLOps/engineering teams to ensure scalable, production-grade model deployment. Stay up to date with new GenAI and ML research trends and identify opportunities for business impact. Mentor junior data scientists and support peer review of code, model design, and documentation. Required Qualifications: Education: Masters or Bachelor's degree in Computer Science, Data Science, Statistics, or related field. Experience: 58 years of professional experience in data science , with proven delivery of ML/AI models in production. Technical Skills: Strong programming skills in Python and use of libraries such as Pandas, Scikit-learn, NumPy, TensorFlow, PyTorch. Experience building and fine-tuning ML models for regression, classification, clustering, or time-series forecasting. Hands-on experience with LLMs and GenAI frameworks (e.g., LangChain, Hugging Face Transformers, OpenAI API, RAG pipelines). Exposure to text embeddings, prompt engineering, vector databases (e.g., FAISS, Pinecone, Chroma). Proficient in using SQL and working with large datasets. Familiarity with model deployment tools and practices (Docker, FastAPI, MLflow, Streamlit, or similar). Experience with cloud platforms (AWS, Azure, or GCP) is a strong plus. Preferred Skills: Experience with NLP, Computer Vision , or time-series modeling . Exposure to MLOps workflows (CI/CD, monitoring, pipeline automation). Familiarity with vector search, RAG architecture , and document intelligence workflows. Previous experience in domains like BFSI, healthcare, retail, or enterprise automation is a plus. Key Attributes: Strong business acumen and stakeholder communication. Ability to balance research mindset with production-readiness . Passion for innovation, continuous learning, and cross-functional collaboration. Team player with mentoring and leadership qualities.

What You'll Do: You will work directly as part of AA CoE and be a part of analytics focused projects across statistics, optimization & simulations, machine learning and Big Data. Your role will involve design and implementation of advanced statistical analysis and machine learning algorithms to derive business insights and solve complex business problems. This includes gathering and analyzing information, formulating and testing hypotheses, and developing and communicating recommendations. You may also be responsible for presenting results to management and implementing recommendations with team members. Youll have the opportunity to gain new skills and build on the strengths you bring to the company. Main task: • Design and implement machine-learning models to support the businesss numerous initiatives and programs with a view of achieving overall objectives and targets • Successful documentation of reusable code • Achieve personal technical development and learning goals • Conduct knowledge sharing sessions internally within the CoE as well as externally in meetups, conferences etc. Participate in and help plan cultural initiatives for CoE Qualifications • University degree in Computer Science, Engineering, Applied Mathematics or related fields and excellent academic record required; Master’s degree in above mentioned subjects preferred • 2-3 years of technical experience in handling large datasets and applying advanced statistical and machine learning algorithms • Hand-on experience in methodologies such as: Supervised and Unsupervised Learning, Feature Engineering, Bayesian Statistics, Frequentist Statistics, Optimization, Time Series, Graph/Network Theory, Reinforcement Learning, Deep Learning, Computer Vision, NLP, Interpretable AI, etc. • Proficiency with at least one of the following languages: R, Python, SAS and experience of working with SQL/NoSQL databases • Experience of working on platforms such as GCP, Dataiku, AWS, Azure, etc. • Stakeholder management skills with ability to communicate and work with senior management effectively • Skills to communicate complex ideas effectively Interested candidates can send their resume on a mail - Resumesktk@muthootgroup.com

Job Description: We are seeking a highly motivated and skilled AI Developer to join our dynamic team. The ideal candidate should have hands-on experience in designing, developing, and deploying AI and machine learning models to solve real-world problems. You will work closely with data scientists, software engineers, and product teams to build intelligent applications. Key Responsibilities: Design and develop AI/ML models based on business requirements Preprocess and analyze structured and unstructured data Implement Deep Learning and NLP algorithms using frameworks like TensorFlow, PyTorch, and Scikit-learn Collaborate with software engineers to integrate models into production environments Build and optimize pipelines for data ingestion, model training, and inference Monitor model performance and retrain as needed Research and implement state-of-the-art algorithms Create dashboards or front-end demos using Streamlit or similar tools (optional) Key Skills Required: Programming: Python (Must), R (Optional), Java (Good to have) AI/ML: TensorFlow, PyTorch, Keras, Scikit-learn Data Science: Pandas, NumPy, Matplotlib, Seaborn NLP: Hugging Face Transformers, NLTK, SpaCy Computer Vision: OpenCV, YOLO, CNNs Model Deployment: Flask, FastAPI, Docker, AWS/Azure/GCP Databases: SQL, MongoDB, Firebase (optional) Version Control: Git, GitHub Preferred Qualifications: Bachelors or Master’s degree in Computer Science, AI, Data Science, or related field Strong mathematical foundation in statistics, linear algebra, and probability Excellent problem-solving skills and attention to detail Strong communication and teamwork skills Why Join Us? Work on cutting-edge AI solutions Collaborative and inclusive work environment Opportunity to grow in a fast-paced tech-driven organization Exposure to real-world enterprise and consumer AI applications

Job Overview: We are seeking a talented and driven Machine Learning Engineer to design and optimize machine learning models that will enhance a variety of credit and operational processes. This role will involve building cutting-edge solutions in areas like underwriting, loan processing, fraud detection, and risk mitigation, while continuously driving improvements through innovation and advanced techniques. Key Responsibilities: - Model Development & OptimizationDesign, deploy, and refine machine learning models to support key functions such as underwriting, account management, fraud detection, and loss prevention. - Advanced Techniques ImplementationIdentify opportunities to implement advanced machine learning approaches-such as Natural Language Processing (NLP), Image Recognition, and Graph Mining-to address complex business challenges. - Collaboration & Knowledge SharingWork with internal and external resources, as well as open-source algorithms, to find the best solutions and improve model performance. - Risk Management CompliancePartner with the Model Risk Management team to ensure models are developed with appropriate rigor and align with risk management and governance standards. - Cross-Functional CollaborationCollaborate closely with Product and Engineering teams to ensure seamless model deployment and integration. - Performance MonitoringTrack the effectiveness of models through dashboards and key performance indicators (KPIs), ensuring continuous improvement. - Stakeholder CommunicationPresent model insights and performance reports to key stakeholders in Credit, Risk, and Business Units, making complex findings accessible and actionable. Qualifications: - Educational BackgroundBachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. A Master's degree is highly preferred. - Experience6-12 years of hands-on experience developing and implementing machine learning models in a professional environment. - Technical ProficiencyStrong expertise in SQL and Python, with the ability to write efficient code for working with large datasets and creating advanced features. - Analytical ThinkingExceptional attention to detail and an ability to uncover hidden data patterns through thorough investigation. - Machine Learning ExpertiseSolid foundation in machine learning and statistical modeling, including supervised and unsupervised learning techniques like regression, decision trees, support vector machines, boosting, deep learning, and more. Must stay current with industry advancements to apply the best techniques. - Database KnowledgeProficient in working with SQL, NoSQL, Hive, and other relevant database technologies. - Effective CommunicationStrong ability to translate complex technical concepts into clear, understandable terms for non-technical stakeholders. Apply Save Save Pro Insights

Skill required:Marketing and Customer Analytics - Data Science Designation:Analytics Associate Manager Job Location:Bengaluru Qualifications:Any Graduation Years of Experience:8 to 12 years 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 to: 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. 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 domains: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 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

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 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. Qualifications Master of Engineering,Masters in Business Economics

Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Sr Analyst Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 5 to 8 years 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. Qualifications Master of Engineering,Masters in Business Economics

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 - AI/Gen AI Retail Specialist Level 9 SnC GN Data & AI 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. Additional Information:

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)

Role Overview: We are seeking a skilled and experienced Data Scientist with a minimum of 3 years of experience, including strong exposure to DevOps tools, AI/ML, and MLOps frameworks. The ideal candidate will work closely with data engineers, machine learning engineers, and product teams to develop, deploy, and maintain machine learning models while ensuring seamless integration with CI/CD pipelines. Key Responsibilities: Design, build, and optimize machine learning models for large-scale datasets. Collaborate with data engineers to preprocess, clean, and organize data for machine learning pipelines. Implement and automate the deployment of machine learning models into production using MLOps practices. Utilize DevOps tools to integrate ML models into continuous integration/continuous deployment (CI/CD) pipelines. Conduct exploratory data analysis, feature engineering, and algorithm selection. Develop and maintain model monitoring and retraining pipelines to ensure optimal model performance over time. Provide data-driven insights and recommendations to product and business teams. Collaborate with cross-functional teams including software developers, data engineers, and DevOps engineers. Required Qualifications: Experience: 3+ years in Data Science, with exposure to AI/ML model development and deployment. Education: Bachelor's or Masters degree in Data Science, Computer Science, Mathematics, Statistics, or a related field. Technical Skills: Proficiency in Python and libraries like Pandas, Scikit-learn, TensorFlow, PyTorch, etc. Strong understanding of machine learning algorithms (supervised/unsupervised learning, reinforcement learning). Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes). Familiarity with DevOps tools such as Jenkins, Git, GitLab CI, or similar for CI/CD integration. Experience with MLOps tools such as MLflow, Kubeflow, or similar for model management and deployment. Experience working with big data frameworks (Hadoop, Spark) is a plus. Knowledge of REST APIs and microservices architecture is a bonus. Soft Skills: Strong problem-solving abilities and analytical thinking. Excellent communication and collaboration skills. Ability to work in a fast-paced environment and manage multiple projects. Nice to Have: Knowledge of NLP, Computer Vision, or deep learning techniques. Experience with version control for models and data pipelines. Prior experience in A/B testing and experiment tracking.

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

Job Title - AI/Gen AI Retail Specialist Level 9 SnC GN Data & AI 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. Additional Information:

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)

Data scientist: Experience: 5-8 years Locations: Hyderabad,Bangalore,Pune,Chennai,Delhi,Kolkatta& Mumbai Immediate joiners Only Role & responsibilities : Job Description: :- Experience creating and using machine learning algorithms and statistics: regression, clustering, decision trees, neural networks, etc. Strong understanding of supervised & unsupervised ML Techniques. Experience statistical computer languages: R, Python etc., Basic knowledge to fetch data from Database like SQL or any cloud resource name it AWS / ADLS Basic knowledge on any Visualization tools like Power BI, Tableau etc., Doing ad-hoc analysis and presenting results in a clear manner. Experience working with and creating data architectures. Strong written and verbal communications skills; comfortable communicating with senior levels of both business and technology leadership. Should be proactive in driving large analytic projects and programs to completion. Explore the big data machine learning models Worked with client projects. Interested candidates can reach out to 7661922227

We are seeking a 'Computer Vision Engineer' to develop AI-driven video analytics solutions for extracting in-depth cricket data from match footage, live broadcasts, and player tracking systems. This role involves leveraging deep learning, pose estimation, and image processing to analyze player movements, shot selection, bowling mechanics, and match dynamics. Key Responsibilities. Video-Based Cricket Analytics. Develop computer vision models for player tracking, ball trajectory prediction, and shot classification. Extract real-time insights from video streams, including player positions, footwork analysis, and batting/bowling techniques. Implement pose estimation (OpenPose, MediaPipe, DeepLabCut) to analyze player body movements. Use action recognition models to classify batting strokes, bowling variations, and fielding plays. Deep Learning & Image Processing. Apply CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. Develop segmentation models to differentiate players, umpires, and key match elements (ball, stumps, pitch zones). Use GANs and super-resolution techniques to enhance low-quality video footage. Build OCR (Optical Character Recognition) systems to extract scoreboards and match statistics from live broadcasts. Real-Time Video Processing & Streaming. Implement real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. Work with multi-angle TV footage and drone feeds to enhance match analysis. Develop low-latency algorithms for real-time ball speed, swing, and spin detection. Data Collection, Annotation & Model Training. Build automated annotation tools for labeling cricket match videos. Train supervised and unsupervised learning models using cricket datasets. Collaborate with sports analysts to validate and refine model predictions. Model Deployment & Performance Optimization. Deploy computer vision models on edge devices, cloud platforms, and real-time streaming systems. Optimize models for low latency and high accuracy in live cricket broadcasts. Implement A/B testing and continuous monitoring to improve model performance. Camera Calibration & Video Trigonometry. Perform camera calibration for distortion correction and real-world coordinate mapping. Use homography transformation and perspective correction for multi-angle alignment. Apply video trigonometry to calculate player distances, ball speed, angles, and movement trajectories. Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About CompanyAt Lifease Solutions LLP, we believe that design and technology are the perfect blend to solve any problem and bring any idea to life. Lifease Solutions is a leading provider of software solutions and services that help businesses succeed. Based in Noida, India, we are committed to delivering high-quality, innovative solutions that drive value and growth for our customers. Our expertise in the finance, sports, and capital market domains has made us a trusted partner for companies around the globe. We take pride in our ability to turn small projects into big successes, and we are always looking for ways to help our clients maximize their IT investments

We are seeking a 'Computer Vision Engineer' to develop AI-driven video analytics solutions for extracting in-depth cricket data from match footage, live broadcasts, and player tracking systems. This role involves leveraging deep learning, pose estimation, and image processing to analyze player movements, shot selection, bowling mechanics, and match dynamics. Key Responsibilities. Video-Based Cricket Analytics. Develop computer vision models for player tracking, ball trajectory prediction, and shot classification. Extract real-time insights from video streams, including player positions, footwork analysis, and batting/bowling techniques. Implement pose estimation (OpenPose, MediaPipe, DeepLabCut) to analyze player body movements. Use action recognition models to classify batting strokes, bowling variations, and fielding plays. Deep Learning & Image Processing. Apply CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. Develop segmentation models to differentiate players, umpires, and key match elements (ball, stumps, pitch zones). Use GANs and super-resolution techniques to enhance low-quality video footage. Build OCR (Optical Character Recognition) systems to extract scoreboards and match statistics from live broadcasts. Real-Time Video Processing & Streaming. Implement real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. Work with multi-angle TV footage and drone feeds to enhance match analysis. Develop low-latency algorithms for real-time ball speed, swing, and spin detection. Data Collection, Annotation & Model Training. Build automated annotation tools for labeling cricket match videos. Train supervised and unsupervised learning models using cricket datasets. Collaborate with sports analysts to validate and refine model predictions. Model Deployment & Performance Optimization. Deploy computer vision models on edge devices, cloud platforms, and real-time streaming systems. Optimize models for low latency and high accuracy in live cricket broadcasts. Implement A/B testing and continuous monitoring to improve model performance. Camera Calibration & Video Trigonometry. Perform camera calibration for distortion correction and real-world coordinate mapping. Use homography transformation and perspective correction for multi-angle alignment. Apply video trigonometry to calculate player distances, ball speed, angles, and movement trajectories. Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About CompanyAt Lifease Solutions LLP, we believe that design and technology are the perfect blend to solve any problem and bring any idea to life. Lifease Solutions is a leading provider of software solutions and services that help businesses succeed. Based in Noida, India, we are committed to delivering high-quality, innovative solutions that drive value and growth for our customers. Our expertise in the finance, sports, and capital market domains has made us a trusted partner for companies around the globe. We take pride in our ability to turn small projects into big successes, and we are always looking for ways to help our clients maximize their IT investments

We are seeking a 'Computer Vision Engineer' to develop AI-driven video analytics solutions for extracting in-depth cricket data from match footage, live broadcasts, and player tracking systems. This role involves leveraging deep learning, pose estimation, and image processing to analyze player movements, shot selection, bowling mechanics, and match dynamics. Key Responsibilities. Video-Based Cricket Analytics. Develop computer vision models for player tracking, ball trajectory prediction, and shot classification. Extract real-time insights from video streams, including player positions, footwork analysis, and batting/bowling techniques. Implement pose estimation (OpenPose, MediaPipe, DeepLabCut) to analyze player body movements. Use action recognition models to classify batting strokes, bowling variations, and fielding plays. Deep Learning & Image Processing. Apply CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. Develop segmentation models to differentiate players, umpires, and key match elements (ball, stumps, pitch zones). Use GANs and super-resolution techniques to enhance low-quality video footage. Build OCR (Optical Character Recognition) systems to extract scoreboards and match statistics from live broadcasts. Real-Time Video Processing & Streaming. Implement real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. Work with multi-angle TV footage and drone feeds to enhance match analysis. Develop low-latency algorithms for real-time ball speed, swing, and spin detection. Data Collection, Annotation & Model Training. Build automated annotation tools for labeling cricket match videos. Train supervised and unsupervised learning models using cricket datasets. Collaborate with sports analysts to validate and refine model predictions. Model Deployment & Performance Optimization. Deploy computer vision models on edge devices, cloud platforms, and real-time streaming systems. Optimize models for low latency and high accuracy in live cricket broadcasts. Implement A/B testing and continuous monitoring to improve model performance. Camera Calibration & Video Trigonometry. Perform camera calibration for distortion correction and real-world coordinate mapping. Use homography transformation and perspective correction for multi-angle alignment. Apply video trigonometry to calculate player distances, ball speed, angles, and movement trajectories. Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About CompanyAt Lifease Solutions LLP, we believe that design and technology are the perfect blend to solve any problem and bring any idea to life. Lifease Solutions is a leading provider of software solutions and services that help businesses succeed. Based in Noida, India, we are committed to delivering high-quality, innovative solutions that drive value and growth for our customers. Our expertise in the finance, sports, and capital market domains has made us a trusted partner for companies around the globe. We take pride in our ability to turn small projects into big successes, and we are always looking for ways to help our clients maximize their IT investments