397 Svm Jobs - Page 2

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Software Engineer II We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Manager Data Scientist AI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency. Opportunity Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate. Role Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases Gather relevant information to define the business problem interfacing with global stakeholders Creative thinker capable of linking AI methodologies to identified business challenges Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models Develop AI/ML solutions/applications leveraging the latest industry and academic advancements Leverage open and closed source technologies to solve business problems Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda Partner with technical teams to implement developed solutions/applications in production environment Support a learning culture continuously advancing AI capabilities Experience All About You Experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Exposure or experience using collaboration tools such as: Confluence (Documentation) Bitbucket/Stash (Code Sharing) Shared Folders (File Sharing) ALM (Project Management) Knowledge of payments industry a plus Experience with SAFe (Scaled Agile Framework) process is a plus Effectiveness Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum Capable of navigating a complex organization in a relentless pursuit of answers and clarity Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment Incredible attention to detail and focus instilling confidence without qualification in developed solutions Core Capabilities Strong written and oral communication skills Strong project management skills Concentration in Computer Science Some international travel required #AI1 Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Senior Data Scientist We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. The Mastercard Launch program is aimed at early career talent, to help you develop skills and gain cross-functional work experience. Over a period of 18 months, Launch participants will be assigned to a business unit, learn and develop skills, and gain valuable on the job experience. Mastercard has over 2 billion payment cards issued by 25,000+ banks across 190+ countries and territories, amassing over 10 petabytes of data. Millions of transactions are flowing to Mastercard in real-time providing an ideal environment to apply and leverage AI at scale. The AI team is responsible for building and deploying innovative AI solutions for all divisions within Mastercard securing a competitive advantage. Our objectives include achieving operational efficiency, improving customer experience, and ensuring robust value propositions of our core products (Credit, Debit, Prepaid) and services (recommendation engine, anti-money laundering, fraud risk management, cybersecurity) Role Gather relevant information to define the business problem Creative thinker capable of linking AI methodologies to identified business challenges Develop AI/ML applications leveraging the latest industry and academic advancements Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda All About You : Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Concentration in Computer Science Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Senior Data Scientist AI Garage is responsible for establishing Mastercard as an AI powerhouse. AI will be leveraged and implemented at scale within Mastercard providing a foundational, competitive advantage for the future. All internal processes, all products and services will be enabled by AI continuously advancing our value proposition, consumer experience, and efficiency. Opportunity Join Mastercard's AI Garage @ Gurgaon, a newly created strategic business unit executing on identified use cases for product optimization and operational efficiency securing Mastercard's competitive advantage through all things AI. The AI professional will be responsible for the creative application and execution of AI use cases, working collaboratively with other AI professionals and business stakeholders to effectively drive the AI mandate. Role Ensure all AI solution development is in line with industry standards for data management and privacy compliance including the collection, use, storage, access, retention, output, reporting, and quality of data at Mastercard Adopt a pragmatic approach to AI, capable of articulating complex technical requirements in a manner this is simple and relevant to stakeholder use cases Gather relevant information to define the business problem interfacing with global stakeholders Creative thinker capable of linking AI methodologies to identified business challenges Identify commonalities amongst use cases enabling a microservice approach to scaling AI at Mastercard, building reusable, multi-purpose models Develop AI/ML solutions/applications leveraging the latest industry and academic advancements Leverage open and closed source technologies to solve business problems Ability to work cross-functionally, and across borders drawing on a broader team of colleagues to effectively execute the AI agenda Partner with technical teams to implement developed solutions/applications in production environment Support a learning culture continuously advancing AI capabilities Experience All About You Experience in the Data Sciences field with a focus on AI strategy and execution and developing solutions from scratch Demonstrated passion for AI competing in sponsored challenges such as Kaggle Previous experience with or exposure to: Deep Learning algorithm techniques, open source tools and technologies, statistical tools, and programming environments such as Python, R, and SQL Big Data platforms such as Hadoop, Hive, Spark, GPU Clusters for deep learning Classical Machine Learning Algorithms like Logistic Regression, Decision trees, Clustering (K-means, Hierarchical and Self-organizing Maps), TSNE, PCA, Bayesian models, Time Series ARIMA/ARMA, Recommender Systems - Collaborative Filtering, FPMC, FISM, Fossil Deep Learning algorithm techniques like Random Forest, GBM, KNN, SVM, Bayesian, Text Mining techniques, Multilayer Perceptron, Neural Networks – Feedforward, CNN, LSTM’s GRU’s is a plus. Optimization techniques – Activity regularization (L1 and L2), Adam, Adagrad, Adadelta concepts; Cost Functions in Neural Nets – Contrastive Loss, Hinge Loss, Binary Cross entropy, Categorical Cross entropy; developed applications in KRR, NLP, Speech and Image processing Deep Learning frameworks for Production Systems like Tensorflow, Keras (for RPD and neural net architecture evaluation), PyTorch and Xgboost, Caffe, and Theono is a plus Exposure or experience using collaboration tools such as: Confluence (Documentation) Bitbucket/Stash (Code Sharing) Shared Folders (File Sharing) ALM (Project Management) Knowledge of payments industry a plus Experience with SAFe (Scaled Agile Framework) process is a plus Effectiveness Effective at managing and validating assumptions with key stakeholders in compressed timeframes, without hampering development momentum Capable of navigating a complex organization in a relentless pursuit of answers and clarity Enthusiasm for Data Sciences embracing the creative application of AI techniques to improve an organization's effectiveness Ability to understand technical system architecture and overarching function along with interdependency elements, as well as anticipate challenges for immediate remediation Ability to unpack complex problems into addressable segments and evaluate AI methods most applicable to addressing the segment Incredible attention to detail and focus instilling confidence without qualification in developed solutions Core Capabilities Strong written and oral communication skills Strong project management skills Concentration in Computer Science Some international travel required Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Matellio is hiring a skilled and visionary AI Lead to drive development of advanced AI solutions. This is a dual role involving both technical leadership and hands-on development —perfect for someone who thrives on solving complex problems with machine learning, NLP, and LLM technologies. Key Responsibilities: Lead and mentor a team of 4–5 AI/ML engineers, guiding them through the full project lifecycle from research to production deployment. Design and own both high-level and low-level architecture for AI and GenAI-based applications, ensuring scalability, performance, and maintainability. Collaborate with sales and business development teams to create technical proposals , including solution design , architecture diagrams , and high-level estimates for Sales Qualified Leads (SQLs). Work as an individual contributor when needed, developing key components of the solution to accelerate delivery and set best practices. Research, design, and implement machine learning and deep learning models, including fine-tuning and deploying LLMs (e.g., GPT, BERT) for production use cases. Build NLP pipelines and retrieval-augmented generation (RAG) systems using tools like LangChain, LangGraph, and vector databases (e.g., FAISS, Pinecone, Weaviate). Apply statistical techniques to feature engineering, model evaluation, and performance optimization. Ensure adherence to code quality, testing, CI/CD, and documentation standards. Stay current with AI/ML advancements and proactively propose innovative solutions. Conduct code reviews, encourage peer learning, and contribute to a strong engineering culture. Required skills and qualifications: Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. 7+ years of hands-on experience in AI/ML model development and deployment. Proven experience in leading technical teams and delivering production-grade AI/ML solutions. Strong architectural skills with experience designing end-to-end solutions involving cloud, APIs, and ML models. Demonstrated experience supporting technical pre-sales efforts through proposals, estimates, and client presentations. Proficient in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn. Hands-on experience with NLP tools like HuggingFace Transformers, SpaCy, and NLTK. Practical knowledge of fine-tuning and deploying LLMs , and building GenAI solutions. Familiarity with LangChain, LangGraph, and vector stores (e.g., FAISS, Pinecone). Strong understanding of classical ML algorithms (SVM, Decision Trees, etc.) and when to use them. Experience deploying models and services using REST APIs, Docker, and CI/CD pipelines. Exposure to cloud platforms such as AWS, GCP, or Azure. Excellent analytical thinking, problem-solving, and communication skills.

As a Manager, Behavioral Modeler (Development/Validation) & Researcher Specialist at Genpact, you will be responsible for developing or validating Behavioral Models for banking and financial institutions, focusing on areas such as Financial Crime (Fraud or AML), Marketing Campaigns, and Adjudication models. Your role will involve working closely with the centralized advanced analytics team of banking or financial firms, interacting with various business units, auditors, and model development/validation teams to ensure compliance with Enterprise Modeling Governance standards. Your key responsibilities will include providing analytical support to mitigate risk, assessing data quality for model development, developing machine learning-based models, proposing recommendations to improve monitoring systems, conducting in-depth research on behavioral modeling policies, and contributing to the creation of whitepapers and artifacts. You will be expected to have hands-on experience in developing and validating models, risk management, and applying AI, ML, and Deep Learning techniques using tools such as SAS, Python, and R. The qualifications we seek in you include a Master's degree in a quantitative discipline, experience in statistical modeling, detailed knowledge of data analysis techniques, expertise in SQL, ETL, and strong scripting and automation skills. Additionally, you should possess strong client management, communication, and presentation skills, be self-driven, proactive, and have the ability to work under ambiguity and with minimal supervision. You should also have strong project management experience, the ability to lead projects and teams, and demonstrate expertise in communicating and coordinating across multiple business units. Preferred qualifications/skills include strong networking, negotiation, and influencing skills, as well as prior experience in financial crime and machine learning models. If you are a forward-thinking individual with a hunger for learning and a passion for turning innovative ideas into reality, we invite you to apply for this challenging and rewarding role at Genpact. Please note that this is a full-time position based in India-Kolkata, and the job posting was on Oct 7, 2024.,

As a candidate for this position, you will be responsible for analysis, design, coding, and integration using C/C++, Python. You should have experience in shadow removal techniques and be familiar with machine learning algorithms such as KNN, SVM, and text search. Additionally, familiarity with tools like QGIS and libraries like OpenCV is expected. The ideal candidate will hold a Master's degree in Machine Learning, Computer Vision, or Deep Learning with GIS knowledge as an add-on qualification. You should possess excellent written and verbal communication skills and be a self-starter with the ability to actively collaborate in a cross-functional team. A problem-solving mindset, along with a passion for technology, creativity, innovation, and resourcefulness, are essential for this role. We are looking for individuals who are eager to learn and innovate in a fast-paced and evolving market. Adaptability to change, a proactive attitude, and a willingness to take on challenges are key attributes we value in our team members. If you are someone who is ready to roll up your sleeves and get things done, we encourage you to apply for this exciting opportunity.,

JOB_POSTING-3-72955 Job Description Role Title: AVP, Analytics Bank (L10) Company Overview Synchrony (NYSE: SYF) is a premier consumer financial services company delivering one of the industry’s most complete digitally enabled product suites. Our experience, expertise and scale encompass a broad spectrum of industries including digital, health and wellness, retail, telecommunications, home, auto, outdoors, pet and more. We have recently been ranked #2 among India’s Best Companies to Work for by Great Place to Work. We were among the Top 50 India’s Best Workplaces in Building a Culture of Innovation by All by GPTW and Top 25 among Best Workplaces in BFSI by GPTW. We have also been recognized by AmbitionBox Employee Choice Awards among the Top 20 Mid-Sized Companies, ranked #3 among Top Rated Companies for Women, and Top-Rated Financial Services Companies. Synchrony celebrates ~52% women talent. We offer Flexibility and Choice for all employees and provide best-in-class employee benefits and programs that cater to work-life integration and overall well-being. We provide career advancement and upskilling opportunities, focusing on Advancing Diverse Talent to take up leadership roles. Organizational Overview Our Analytics organization comprises of data analysts who focus on enabling strategies to enhance customer and partner experience and optimize business performance through data management and development of full stack descriptive to prescriptive analytics solutions using cutting edge technologies thereby enabling business growth Role Summary/Purpose AVP, Analytics Bank (People Manager & Individual Contributor) is a part of India Analytics Hub (IAH). The role will be responsible for managing deposits business, provide thought leadership and drive solutions with business impact. The role will deliver high-visibility and high-impact projects, working in close collaboration with IAH and US Analytics teams to help solve key business problems with solutions that are powered by data and analytics. Key Responsibilities Proactively propose, initiate & execute strategic projects that create business impact and to facilitate decision making Lead & manage the development of team members. Mentor them on Analytical and Technical skills. Be hands on and willing to roll up sleeve to help deliver projects Develop marketing strategies aligned with bank goals to drive new applications and accounts and increase balances and retention Develop proformas to support different tests & use cases. Drive team to leverage & explore latest tools and techniques in the industry and leverage them for business growth. Initiate ideas to drive usage of open source tools Proactively discuss the projects, showcase & drive for implementation and gauge the business impact. Work with cross-functional teams to facilitate the data collection and performance measurement process and escalate issues as necessary and make contributions to research and analyses on priority projects within established guidelines. Deliver projects adhering timelines, accuracy & compliance with meticulous project management. Proactively leverage expertise of team members to deploy the resources as per skillset Proactive & regular communication with Stakeholders on Projects & People Create a team culture and interactive environment that can also incorporate fun Willing to upskill on digital tools such as Google 360 suite is required Acquire proficiency on varied data and analytic tools, software, techniques to improve current capabilities, create new analytics/data science solutions and proactively exhibit thought leadership Contribute to internal initiatives, perform other duties and/or special projects, as assigned Required Skills & Knowledge Degree in Statistics, Mathematics, Economics, Engineering, or any other quantitative streams with 4+ years of hands-on relevant analytics/data science experience. Minimum 6+ years of relevant work experience in lieu of specified degree. Minimum 4 years of hands-on SQL and SAS programming experience with an ability to leverage advanced algorithms and be efficient in handling complex/large data sets Minimum 3 years of experience in leveraging data/analytics to drive strategy with positive outcomes Drive business growth by conceptualizing and executing strategic projects, facilitate key meetings, and mentoring the team to unlock their full potential Good working knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Advanced proficiency in MS-Excel and MS-PowerPoint with superior data analyses and story boarding skills Desired Skills & Knowledge 4+ years of analytics/data science experience in Financial Services Industry Experience in working SAS and exposure to Python Ability to drive initiatives Good understanding of US consumer banking business Knowledge of latest Analytics Data Visualization tools like Tableau Knowledge of multivariable calculus and linear algebra with predictive performance or algorithm optimization techniques, ML methods like k-Nearest Neighbors, Naive Bayes, SVM, Random Forest, etc. Eligibility Criteria Degree in Statistics, Mathematics, Economics, Engineering, or any other quantitative streams with 4+ years of hands-on relevant analytics/data science experience. Minimum 6+ years of relevant work experience in lieu of specified degree. Work Timings: 2 pm to 11 pm IST The position is remote, where you have the option to work from home. For Internal Applicants Understand the criteria or mandatory skills required for the role, before applying Inform your manager and HRM before applying for any role on Workday Ensure that your professional profile is updated (fields such as education, prior experience, other skills) and it is mandatory to upload your updated resume (Word or PDF format) Must not be any corrective action plan (First Formal/Final Formal, LPP) L8+ Employees who have completed 18 months in the organization and 12 months in current role and level are only eligible. L08+ Employees can apply Grade/Level: 10 Job Family Group Data Analytics

AI/ML Engineer Responsibilities: - Design, build, and deploy advanced machine learning models and algorithms to solve complex problems in various domains, such as natural language processing, computer vision, and predictive analytics. - Collaborate closely with cross-functional teams, including data scientists, engineers, and product managers, to identify opportunities for leveraging company data to improve business outcomes. - Perform data mining and feature extraction using advanced statistical and machine learning techniques. - Evaluate and validate the performance of machine learning models using appropriate metrics and techniques. - Optimize and fine-tune machine learning models for optimal performance in production environments. - Stay up-to-date with the latest advancements in machine learning and artificial intelligence research. - Contribute to the development of best practices in machine learning and share knowledge with peers and junior team members. - Provide technical leadership and mentoring to other team members as needed. Requirements: - 4+ years of experience in developing and deploying machine learning models in a professional setting. - Strong understanding of various machine learning algorithms, such as linear regression, logistic regression, decision trees, SVM, neural networks, ensemble methods, and reinforcement learning. - Demonstrated experience in working with large datasets and using big data technologies, such as Hadoop, Spark, and distributed computing. - Proficient in programming languages, such as Python. - Experience with machine learning frameworks and libraries, such as TensorFlow, Keras, PyTorch, or Scikit-learn. - Familiarity with data visualization tools, such as Tableau, Matplotlib, or D3.js. Preferred Qualifications: - Experience in working with cloud platforms, such as AWS, Google Cloud, or Azure. - Knowledge of natural language processing, computer vision, or deep learning techniques. - Experience developing end-to-end machine learning pipelines, from data gathering and preprocessing to model deployment and monitoring.

We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that is bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com. What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it? We understand that you are looking for growth and variety in your career at this point and we would love for you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We hire the best and trust them from day 1 to deliver global impact, handle teams and be responsible for the outcomes while our leaders support and mentor you. We are a profitable rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology. We offer global opportunities with fast-track careers while you work with a team that is fueled by purpose. The combination of these will lead to a truly differentiated experience for you. If this excites you, then apply below. Role: Senior Analyst - Data Science Descriptions: We are looking for a results-driven and hands-on Lead Data Scientist / Analyst with 56 years of experience to lead analytical solutioning and model development in the pharmaceutical commercial analytics domain. The ideal candidate will play a central role in designing and deploying Decision Engine frameworks, implementing advanced analytics solutions, and mentoring junior team members. Key Responsibilities Partner with cross-functional teams and client stakeholders to gather business requirements and translate them into robust ML/analytical solutions. Design and implement Decision Engine workflows to support Next Best Action (NBA) recommendations in omnichannel engagement strategies. Analyze large and complex datasets across sources like APLD, sales, CRM, call plans, market share, patient claims, and segmentation data. Perform ad hoc and deep-dive analyses to address critical business questions across commercial and medical teams. Develop, validate, and maintain predictive models for use cases such as patient journey analytics, HCP targeting, sales forecasting, risk scoring, and marketing mix modeling. Implement MLOps pipelines using Dataiku, Git, and AWS services to support scalable and repeatable deployment of analytics models. Ensure data quality through systematic QC checks, test case creation, and validation frameworks. Lead and mentor junior analysts and data scientists in coding best practices, feature engineering, model interpretability, and cloud-based workflows. Stay up to date with industry trends, regulatory compliance, and emerging data science techniques relevant to life sciences analytics. Must Have 5 years of hands-on experience in pharmaceutical commercial analytics, with exposure to cross-functional brand analytics, omnichannel measurement, and ML modeling. At least 3 years of experience developing and deploying predictive models and ML pipelines in real-world settings. Proven experience with data platforms such as Snowflake, Dataiku, AWS, and proficiency in PySpark, Python, and SQL. Experience with MLOps practices, including version control, model monitoring, and automation. Strong understanding of pharmaceutical data assets (e.g., APLD, DDD, NBRx, TRx, specialty pharmacy, CRM, digital engagement). Proficiency in ML algorithms (e.g., XGBoost, Random Forest, SVM, Logistic Regression, Neural Networks, NLP). Experience in key use cases: Next Best Action, Recommendation Engines, Attribution Models, Segmentation, Marketing ROI, Collaborative Filtering. Hands-on expertise in building explainable ML models and using tools for model monitoring and retraining. Familiarity with dashboarding tools like Tableau or PowerBI is a plus. Strong communication and documentation skills to effectively convey findings to both technical and non-technical audiences. Ability to work in a dynamic, fast-paced environment and deliver results under tight timelines. EQUAL OPPORTUNITY Indegene is proud to be an Equal Employment Employer and is committed to the culture of Inclusion and Diversity. We do not discriminate on the basis of race, religion, sex, colour, age, national origin, pregnancy, sexual orientation, physical ability, or any other characteristics. All employment decisions, from hiring to separation, will be based on business requirements, the candidates merit and qualification. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristics. Locations - Bangalore, KA, IN

Job Description - Jr. Data Scientist Experience: 0-1 year | Employment Type: Full-time Overview We are looking for a motivated Data Scientist with foundational data science expertise. This position is ideal for recent graduates or early-career professionals eager to work with real-world data, applying both standard and advanced preprocessing and modeling techniques in a collaborative environment. PLEASE NOTE: Mandatory: Email your CV to careers@solvusai.com with the subject line: “Job ID 202507-DS01: ” This is a full-time role with a hybrid work model Students currently pursuing a degree should not apply A strong foundation and clear understanding of data science concepts is essential Key Responsibilities 1. Data Ingestion & Preparation Extract and manipulate data using SQL and Python (pandas) Import and clean both structured & unstructured datasets 2. Data Preprocessing & Feature Engineering Handle missing values, outliers, and duplicates using statistical and ML techniques Apply noise reduction, data integration, and transformation (e.g., scaling, encoding) Perform dimensionality reduction (e.g., PCA) and ensure quality through data validation 3. Model Building & Evaluation Develop machine learning models (e.g., Linear Regression, Random Forest, XGBoost, ARIMA, LSTM) for varied problem types Tune hyperparameters using cross-validation and assess models using standard metrics (accuracy, RMSE, F1-score, etc.) 4. Visualization & Insight Generation Build dashboards and visualizations using tools like Matplotlib, Seaborn, Plotly, or Tableau Conduct statistical analysis to derive actionable business insights and present findings clearly 5. Team Collaboration Work closely with cross-functional teams (data engineers, analysts, business units) to align deliverables with organizational goals Participate in agile discussions and contribute to iterative development Required Skills Bachelors or Masters in Data Science, Computer Science, Statistics, or related field Proficiency in Python or R Strong SQL skills for data extraction/manipulation from relational databases Experience handling CSV/Excel data ingestion; advanced data cleaning techniques Understanding and implementation of various machine learning models (e.g., Linear Regression, Decision Tree, Random Forest, XGBoost, ARIMA, LSTM, SVM, K-Means) and their practical applications Ability to evaluate model performance using appropriate metrics: accuracy, precision, recall, F1-score, RMSE, MAE, ROC-AUC, etc Experience with feature scaling and categorical variable encoding Data visualization using Matplotlib, Seaborn, Plotly, or Tableau Analytical thinking, problem-solving, teamwork, and clear communication Ready to make an impact by transforming data into meaningful insights? Apply now!

As an AI/ML Developer at our company in Meerut, you will utilize your 2 to 5 years of hands-on experience to design, build, and deploy machine learning models. Your main responsibilities will include developing models for various tasks like classification, regression, clustering, or NLP/computer vision. You will collaborate with cross-functional teams to understand business requirements and implement AI/ML solutions accordingly. Your expertise in Python libraries such as Pandas, NumPy, and Scikit-learn will be crucial in cleaning, preprocessing, and analyzing large datasets. Additionally, you will work with deep learning frameworks like TensorFlow, PyTorch, or Keras to fine-tune models for optimal performance, accuracy, and scalability. Developing APIs or services for model deployment and monitoring post-deployment performance will also be part of your responsibilities. To excel in this role, you should hold a Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field. Your strong proficiency in Python and experience with ML algorithms and evaluation metrics will be essential. Exposure to deep learning frameworks and tools like Flask, FastAPI, Docker, or AWS SageMaker will be advantageous. Knowledge of SQL, NoSQL databases, version control tools like Git, and cloud platforms like AWS/GCP/Azure will also be beneficial. Keeping yourself updated with the latest advancements in AI/ML research and techniques is encouraged to contribute effectively to our projects. If you are passionate about leveraging AI and ML technologies to drive innovation and solve real-world problems, we invite you to join our dynamic team and make a meaningful impact in the field.,

🚀 We’re Hiring: Sr. Consultant – Data Science (Remote) 📍 Location : Remote 📊 Analytics Experience : 8–12 Years 🧠 Machine Learning/Data Science : Min. 7 Years Are you passionate about solving real-world business problems using advanced analytics and machine learning? We’re looking for a Senior Consultant – Data Science with deep hands-on expertise and leadership skills. ✅ Role Requirements: 🔹 6+ years of experience building statistical models and handling end-to-end analytics projects 🔹 Strong command over Python and SQL 🔹 Hands-on experience with visualization tools like Power BI or Tableau 🔹 Experience with both structured and unstructured data using classification, regression, clustering, NLP, etc. 🔹 Worked closely with clients on analytics opportunity identification, roadmap development, and solution delivery 🔹 Exposure to at least two sectors: Healthcare , Banking , Financial Services , Insurance , E-Commerce 💡 Technical Skills: Proficiency in ML techniques: Decision Trees, Random Forest, SVM, Naïve Bayes, KNN, PCA, Clustering Text Mining: Entity extraction, sentiment analysis, document summarization Exposure to ETL , Salesforce/CRM integration, and data visualization Bonus: Working knowledge of Generative AI. 📩 Interested? Share your profile at kalpanadeshmukh@livecjobs.com 📞 Or connect with us directly: 7386971110 Let’s build something impactful together! #Hiring #DataScience #MachineLearning #AnalyticsJobs #RemoteJobs #SeniorConsultant #AI #Leadership #GenerativeAI #LivecJobs

Senior Data Science Lead Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements JD is below: The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. ________________________________________ Key Responsibilities 1. Architecting & Scaling Agentic AI Solutions Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. ________________________________________

Senior Data Science Lead Primary Skills Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio Job requirements JD is below: The Agentic AI Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. ________________________________________ Key Responsibilities 1. Architecting & Scaling Agentic AI Solutions Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents. ________________________________________

Silverpush is at the forefront of AI-powered video advertising, delivering sophisticated video ad solutions that empower brands to achieve impactful campaigns within a privacy-centric environment. Operating across 30+ countries, we specialize in creating contextually relevant advertising experiences that drive genuine engagement and conversion. Silverpush's commitment to innovation and technological advancement enables us to navigate the evolving digital landscape, providing our partners with the tools necessary to connect with audiences on a global scale. We are dedicated to fostering a culture of creativity and excellence, driving the future of ad tech with integrity and foresight. For more information about Silverpush’s innovative advertising solutions, please visit www.silverpush.co. Responsibilities: ● Analyze complex datasets to identify trends, patterns, and correlations, and extract actionable insights that can inform strategic decisions. ● Design and build predictive models using statistical and machine learning techniques (e.g., regression, classification, XGBoost, clustering). ● Research and develop analyses and forecasting and optimization methods across ads performance, content performance modeling, and live experiments. ● Research and prototype using cutting-edge LLM technologies and generative AI to unlock new opportunities in personalization, targeting, and automation. Ideal Candidate Profile ● 3+ years of experience in Data Science, ideally in advertising or media-related domains. ● Degree in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Masters in DS). ● Deep experience working with large-scale structured and unstructured data. ● Strong foundation in machine learning and statistical modeling. ● Familiar with building and deploying models in production (basic MLOps knowledge). ● Comfortable with NLP and computer vision, and interested in applying LLMs to real-world use cases. ● Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders. Technical Skills ● Languages & Tools: Python, PySpark, SQL ● ML Techniques: Regression, Classification, Clustering, Decision Trees, Random Forests, XGBoost, SVM ● LLM Tech: Familiarity with tools like OpenAI, Hugging Face, LangChain, and prompt engineering ● Data Infrastructure: ETL tools, Postgres, BigQuery/Snowflake, S3/GCP ● Statistical Analysis: A/B testing, experiment design, causal inference

About The Role We are seeking a highly motivated and experienced Senior Data Scientist to join our growing data science team. This role is ideal for someone who thrives at the intersection of business and technology, has a strong foundation in machine learning, and can drive impactful AI initiatives from concept to production. The ideal candidate will have exposure to the metal or manufacturing industry and is proficient in working with cloud-based ML solutions (preferably Azure). Key Responsibilities Translate complex business problems into data science solutions by working closely with business stakeholders, product teams, and domain experts. Conduct problem scoping, solution framing, and feasibility assessments to define clear ML project goals and success metrics. Perform in-depth exploratory data analysis (EDA) to uncover hidden insights and relationships in large, high-dimensional datasets. Design and implement robust data preprocessing and feature engineering pipelines, using both structured and unstructured data. Develop and validate scalable, production-grade ML models including traditional ML (Random Forests, Gradient Boosting, SVM) and deep learning models (CNNs, RNNs, Transformers). Deploy, monitor, and maintain ML models in production environments using Azure ML (preferred), AWS Sagemaker, or Google Vertex AI. Implement end-to-end ML pipelines integrating data ingestion, preprocessing, training, evaluation, deployment, and monitoring (MLOps). Write clean, reusable, and well-documented code in Python following industry standards and MLOps principles (e.g., CI/CD, model versioning, automated testing). Use version control (e.g., Git), experiment tracking tools (e.g., MLflow), and containerization (Docker/Kubernetes) where applicable. Present technical concepts, insights, and recommendations to business and technical stakeholders in a clear and effective manner. Lead client engagements and influence decision-making through storytelling, data visualization, and domain-specific insights. Mentor and guide junior data scientists on technical approaches, project planning, and model evaluation. Foster a culture of innovation, collaboration, and continuous learning across cross-functional teams. Qualifications Bachelors or Masters degree in Metallurgy, Mechanical Engineering, Computer Science, Information Technology, or related disciplines from a top-tier institution (IIT/NIT or equivalent). 4+ years of hands-on experience in data science, machine learning, or applied AI. Prior work in manufacturing, metallurgy, or industrial domains is highly desirable. Proven track record of building and deploying machine learning solutions at scale (ref:hirist.tech)

We are looking for an experienced Data Scientist with a strong background in Retail & E-commerce Analytics , particularly in integrating offline store data into analytics solutions. The ideal candidate will leverage General Analytics , AI/ML , and other advanced data science techniques to bridge the gap between online and offline retail data, enabling smarter business decisions and enhancing customer experiences across both channels. Responsibilities: Offline Store Data Analytics : Analyze and integrate offline store data (sales, foot traffic, inventory, etc.) with online data to provide a holistic view of customer behavior and sales trends. Use AI/ML models to optimize offline store performance by forecasting demand, inventory needs, and staffing levels based on historical data. Analyze the impact of offline marketing campaigns and promotions on in-store foot traffic and sales, using predictive analytics and machine learning. Develop models to predict store performance, taking into account various factors like location, weather, local events, and other external variables. Retail & E-commerce Analytics : Use machine learning algorithms and statistical analysis to understand and predict consumer behavior, both in-store and online. Build and maintain models for customer segmentation , personalized marketing , and sales forecasting for both e-commerce and brick-and-mortar stores. Identify key metrics for store performance and customer satisfaction, helping management teams optimize strategies for in-store and online experiences. AI/ML Implementation For Retail Optimization : Apply AI/ML techniques (e.g., classification , regression , clustering , time series forecasting ) to retail data, enabling actionable insights for improving product assortment, pricing, and promotions both online and offline. Develop demand forecasting models for offline stores , ensuring optimal stock levels based on predicted customer needs and sales trends. Use machine learning to enhance inventory management in offline stores by predicting inventory shortages and surplus. Data Integration & Visualization : Work with large datasets from both offline and online sources to clean, integrate, and analyze the data, ensuring data accuracy and consistency. Develop dashboards and visualizations using tools like Tableau , Power BI , or Google Data Studio to communicate key findings and business insights to stakeholders. Create reports that combine insights from offline and online channels, providing a unified view of retail operations. Campaign Performance Analysis : Use data science techniques to analyze the effectiveness of offline marketing campaigns and promotions on both in-store and online traffic, conversion rates, and sales. Evaluate customer engagement with offline campaigns, offering insights into how online and offline channels influence each other. Collaboration With Cross-Functional Teams : Work closely with retail managers, marketing teams, and IT teams to implement data-driven solutions that improve customer experience and business performance. Collaborate with product, marketing, and supply chain teams to optimize the omnichannel strategy , including aligning online and offline inventories and promotions. Key Technical Skills: Machine Learning & AI : Proficiency in Python or R for building and deploying AI/ML models such as random forests , XGBoost , SVM , and neural networks . Strong experience in applying predictive modeling , regression analysis , and time series forecasting to retail data, including demand forecasting and sales prediction. Familiarity with deep learning techniques (e.g., RNNs , LSTMs ) for more complex data patterns, if relevant. Retail & E-commerce Analytics : Experience in analyzing point-of-sale (POS) data , foot traffic data , and customer journey data for offline retail stores. Understanding of e-commerce KPIs and how they integrate with offline store performance metrics. Strong knowledge of inventory optimization , supply chain management , and how they relate to both online and offline retail operations. Big Data & Data Integration : Proficiency in handling and analyzing large datasets from multiple sources (online and offline) using SQL , NoSQL , and cloud platforms like AWS , GCP , or Azure . Ability to work with ETL processes to integrate data from multiple systems, ensuring high-quality data for analysis. Data Visualization & Reporting : Experience with Tableau , Power BI , Google Data Studio , or other visualization tools to present insights and actionable business recommendations. Strong communication skills to present complex findings to both technical and non-technical stakeholders. Statistical Analysis : Proficiency in statistical methods for hypothesis testing, segmentation analysis, and measuring the effectiveness of retail strategies and campaigns. Familiarity with advanced statistical techniques, including Bayesian methods , Monte Carlo simulations , and multivariate testing . Desired Qualifications: Bachelor’s or Master’s degree in Computer Science , Data Science , Statistics , Engineering , or a related field. 5+ years of experience in data science or analytics in the retail or e-commerce industry, with a focus on offline store performance . Proven experience in applying AI/ML models to solve real-world business problems, including demand forecasting, personalization, and campaign optimization. Familiarity with offline store data (sales, foot traffic, inventory) and how it integrates with e-commerce platforms . Strong understanding of the retail industry, particularly in optimizing performance across omnichannel environments (online and offline).

The Senior Data Science Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. Key Responsibilities: 1. Architecting & Scaling Agentic AI Solutions: - Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. - Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. - Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization: - Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. - Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. - Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research: - Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. - Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. - Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact: - Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. - Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building: - Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. - Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents.,

As a skilled and visionary AI Lead at Matellio, you will be responsible for driving the development of advanced AI solutions. This dual role will require you to provide technical leadership and hands-on development expertise, making it an ideal position for individuals who excel at solving complex problems using machine learning, NLP, and LLM technologies. Your key responsibilities will include leading and mentoring a team of 45 AI/ML engineers, overseeing the entire project lifecycle from research to production deployment. You will be tasked with designing and owning high-level and low-level architecture for AI and GenAI-based applications, ensuring scalability, performance, and maintainability. Collaboration with sales and business development teams to create technical proposals, solution designs, and architecture diagrams for Sales Qualified Leads (SQLs) will also be part of your role. Additionally, you will work as an individual contributor when necessary, focusing on developing key components of solutions to accelerate delivery and establish best practices. Your responsibilities will extend to researching, designing, and implementing machine learning and deep learning models, including fine-tuning and deploying LLMs like GPT and BERT for production use cases. Building NLP pipelines and retrieval-augmented generation (RAG) systems using tools such as LangChain, LangGraph, and vector databases like FAISS, Pinecone, and Weaviate will also be crucial. You will be expected to apply statistical techniques to feature engineering, model evaluation, and performance optimization, ensuring adherence to code quality, testing, CI/CD, and documentation standards. Staying up-to-date with the latest advancements in AI/ML and proposing innovative solutions will be essential. Conducting code reviews, promoting peer learning, and fostering a strong engineering culture will also be part of your responsibilities. To qualify for this role, you should hold a Bachelors, Masters, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. Additionally, you should have at least 7 years of hands-on experience in AI/ML model development and deployment. Proven expertise in leading technical teams and delivering production-grade AI/ML solutions is required. Strong architectural skills with experience in designing end-to-end solutions involving cloud, APIs, and ML models are essential. Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and scikit-learn is necessary, along with hands-on experience in NLP tools like HuggingFace Transformers, SpaCy, and NLTK. Practical knowledge of fine-tuning and deploying LLMs, as well as building GenAI solutions, is expected. Familiarity with tools like LangChain, LangGraph, and vector stores (e.g., FAISS, Pinecone) will be advantageous. A solid understanding of classical ML algorithms (SVM, Decision Trees, etc.) and when to utilize them, experience deploying models and services using REST APIs, Docker, and CI/CD pipelines, and exposure to cloud platforms such as AWS, GCP, or Azure are highly desirable. Excellent analytical thinking, problem-solving, and communication skills will be crucial for success in this role.,

As an AI/ML Developer at our Gurugram location, you will be responsible for designing and implementing end-to-end machine learning models using Python for various tasks such as regression, classification, clustering, NLP, and deep learning. Your expertise in developing AI applications based on Machine Learning and Large Language Model (LLM) using tools like LangChain, RAG pipelines, vector databases, and more will be crucial in driving AI innovation. You will work on building and deploying AI applications leveraging technologies such as Retrieval Augmented Generation (RAG), LangChain, LLMs (OpenAI, Huggingface Transformers), and Vector Databases (FAISS, Pinecone, Milvus). Your role will involve developing robust pipelines for semantic search and retrieval chains in real-world production systems, writing clean and efficient Python code, and collaborating with cross-functional teams to deliver scalable AI/ML solutions. If you have front-end skills in React, it would be considered a big plus as you may also contribute to UI components for interactive AI applications. To be successful in this role, you should have at least 5 years of hands-on experience in AI/ML development using Python and a strong knowledge of ML algorithms such as XGBoost, SVM, Random Forests, Logistic Regression, as well as deep learning models like CNNs, RNNs, Transformers (BERT, GPT), and unsupervised learning techniques including K-Means and PCA. Experience with RAG architecture, LangChain, advanced prompt engineering, vector search techniques, and Python libraries like scikit-learn, TensorFlow, PyTorch, and Huggingface Transformers is essential. Proficiency in working with cloud environments such as AWS, Azure, or GCP is also required. It would be nice to have front-end development experience using React.js, familiarity with MLOps tools like MLflow, Kubeflow, Airflow, and knowledge of self-supervised or contrastive learning methods such as SimCLR and CLIP. In this role, you will have the opportunity to work on cutting-edge AI/ML technologies, collaborate in a fast-paced and innovative environment, contribute to impactful production-level AI solutions, and enjoy competitive compensation and benefits.,

Posted on 23.07.2025 What’s important to us: Techversant is seeking experienced Data Scientist Engineers who will be responsible for developing and driving new business opportunities internationally. The incumbent will be responsible for discovering sales opportunities and creating qualified leads. Job Description Key Responsibilities Data mining or extracting usable data from valuable data sources Using machine learning tools to select features, create and optimize classifiers Carrying out the preprocessing of structured and unstructured data Enhancing data collection procedures to include all relevant information for developing analytic systems Processing, cleansing, and validating the integrity of data to be used for analysis Analyzing large amounts of information to find patterns and solutions Developing prediction systems and machine learning algorithms Presenting results in a clear manner Propose solutions and strategies to tackle business challenges Collaborate with Business and IT teams Required Skills Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage. Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies. Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests. Strong Math Skills (Multivariable Calculus and Linear Algebra) – understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques. Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description. Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., Tableau that help to visually encode data Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience. Strong Software Engineering Background Hands-on experience with data science tools Problem-solving aptitude Analytical mind and great business sense Degree in Computer Science, Engineering or relevant field is preferred Proven Experience as Data Analyst or Data Scientist What Company Offers: Excellent career growth opportunities and exposure to multiple technologies. Fixed weekday day schedule, meaning, you’ll have your weekends off! Family Medical Insurance. Unique leave benefits and encashment options based on performance. Long term growth opportunities. Fun family environment surrounded by experienced developers. Various internal employee rewards programs based on Performance. Opportunities for various other Bonus programs – for training hours taken, certifications, special value to business through idea and innovation. Work life Balance – flexible work timings, early out Fridays, various social and cultural activities etc. Company Sponsored International Tours. Email to careers@techversantinfotech.com

Job description Out of the box thinker to build innovative AI/ML models : 1. Understand and analyze requirements requiring Machine Learning Models from Product Owners, Customers, and Other Stakeholders 2. Analyze and verify data quality and features 3. Design solutions by choosing the right algorithms, features, and hyperparameters 4. Manage the full lifecycle of ML Models: Data Acquisition, Feature Engineering, Model Development, Training, Verification, Optimization, Deployment, Versioning 5. Augment Enterprise data with publicly available datasets to enrich models features 6. Create strategies for integrating Whiz.AI platform with external enterprise data sources like Databases, Data Warehouses, Analytical Stores, External ML Systems/Algorithms, Hadoop and ERP/CRM systems. Qualifications Technical 5+ years of experience in implementing Machine Learning and Deep Learning models applied to traditional as well as NLP problems Machine Learning-based models: ANN, SVM, Logistic Regression, Gradient Boosting Time Series Anomaly Detections Methods, Hierarchical or Grouped Time Series Forecasting Knowledge of BERT, LSTMs, RNNs, and HMMs applied to Text classification and Text Generation problems Understanding of ML Data processing frameworks like TensorFlow or PyTorch, XGBoost, SciPy, Scikit-Learn, Apache Spark SQL and handling Big Data, databases Excellent knowledge of Python Programming, NumPy, Pandas, and processing JSON, XML, CSV files Non-Technical Good communication analytical skills Self-driven with a strong sense of ownership urgency Preferred Qualifications Preference will be given to the hands-on Deep Learning and NLP application experience Knowledge of Analytical/OLAP/Columnar, Hadoop Ecosystem and NoSQL databases Deep Learning, GANs, Reinforcement Learning R programming, Matlab Knowledge of Lifesciences or Pharmaceutical Industry dataset Interested candidate can share resume at shwetachouhan@valere.io Job Type: Full-time Pay: From ₹1,500,000.00 per year Benefits: Health insurance Paid sick time Paid time off Provident Fund Education: Bachelor's (Preferred) Experience: software development: 1 year (Preferred) HTML5: 1 year (Preferred) total work: 5 years (Preferred) Work Location: In person

The Smart Cube, a WNS company, is seeking Assistant Managers who will collaborate with the Project Lead to design effective analytical frameworks aligned with client objectives. The Assistant Managers will translate requirements into clear deliverables, manage data preparation, perform quality checks, and ensure analysis readiness. They should possess expertise in implementing analytical techniques and machine learning methods such as regression, decision trees, segmentation, forecasting, and algorithms like Random Forest, SVM, and ANN. Additionally, they are responsible for sanity checks, quality control, and interpreting results in a business context to identify actionable insights. Assistant Managers will independently handle client communications, interact with onsite leads, and manage the entire project lifecycle from initiation to delivery. This includes translating business requirements into technical specifications, overseeing data teams, ensuring data integrity, and facilitating communication between business and technical stakeholders. They will lead process improvements in analytics and act as project leads for cross-functional coordination. In terms of client management, Assistant Managers will serve as client leads, maintain strong relationships, participate in deliverable discussions, and guide project teams on execution strategies. Proficiency in connecting databases with Knime, understanding SQL concepts, and designing Knime ETL workflows to support BI tools is required. They must also be proficient in PowerBI for building dashboards and supporting data-driven decision-making. Knowledge of leading analytics projects using PowerBI, Python, and SQL to generate insights is essential. Ideal candidates should have 4-7 years of experience in advanced analytics across Marketing, CRM, or Pricing in Retail or CPG. Experience in other B2C domains is also acceptable. Proficiency in handling large datasets using Python, R, or SAS, and experience with multiple analytics or machine learning techniques is required. Candidates should have a good understanding of consumer sectors such as Retail, CPG, or Telecom, and experience with various data formats and platforms including flat files, RDBMS, Knime workflows and server, SQL Server, Teradata, Hadoop, and Spark. Strong written and verbal communication skills are essential for creating client-ready deliverables using Excel and PowerPoint. Basic knowledge of statistical and machine learning techniques like regression, clustering, decision trees, forecasting, and other ML models is also necessary. Knowledge of optimization methods, supply chain concepts, VBA, Excel Macros, Tableau, and Qlikview will be an added advantage. Qualifications: - Engineers from top tier institutes (IITs, DCE/NSIT, NITs) or Post Graduates in Maths/Statistics/OR from top Tier Colleges/Universities - MBA from top tier B-schools,

Job Description- We are committed to creating a workplace for the industry’s best talent. The Smart Cube (A WNS Company) is proud to be certified as a ‘Great Place to Work’ for the fifth year running. The Smart Cube is also recognized by Great Place to Work as One of India’s Best Workplaces for Women 2021. The Smart Cube, a global provider of strategic research and analytics solutions, has been rated on Analytics India Magazine’s (AIM) Penetration and Maturity Quadrant of Top Data Science Providers as a “Seasoned Vendor” 2022 report amongst the leading analytics service providers based out of India. We are listed in top 50 data science organization The Smart Cube shortlisted for two awards at the British Data Awards. Our clients include a third of the companies in the FTSE and Fortune 100, primarily in the CPG, Life Sciences, Energy, Chemicals, Industrials, Financial Services, Professional Services, and Retail sectors. Roles and responsibilities Specifically, Assistant Managers should – Understand the client objectives, and work with the Project Lead (PL) to design the analytical solution/framework. Be able to translate the client objectives / analytical plan into clear deliverables with associated priorities and constraints Organize/Prepare/Manage data and conduct quality checks to ensure that the analysis dataset is ready Explore and implement various statistical and analytical techniques (including machine learning) like linear/non-linear Regression, Decision Trees, Segmentation, time series forecasting as well as machine learning algorithms like Random Forest, SVM, ANN, etc. Conduct sanity checks of the analysis output based on reasoning and common sense, and be able to do a rigorous self QC, as well as of the work assigned to junior analysts to ensure an error free output Interpret the output in context of the client’s business and industry to identify trends and actionable insights Be able to take client calls relatively independently, and interact with onsite leads (if applicable) on a daily basis Discuss queries/certain sections of deliverable report over client calls or video conferences Oversee the entire project lifecycle, from initiation to closure, ensuring timely and within-budget delivery. Collaborate with stakeholders to gather and refine business requirements, translating them into technical specifications. Manage a team of data analysts and developers, providing guidance, mentorship, and performance evaluations. Ensure data integrity and accuracy through rigorous data validation and quality checks. Facilitate effective communication between technical teams and business stakeholders to align project goals and expectations. Drive continuous improvement initiatives to enhance data analytics processes and methodologies. Act as a project lead, coordinating cross-functional teams and managing project timelines and deliverables. Client Management Act as client lead and maintain client relationship; make independent key decisions related to client management Be a part of deliverable discussions with clients over telephonic calls, and guide the project team on the next steps and way forward Technical Requirements: Knowledge of how to connect Database with Knime e.g. snowflake, SQL db etc. along with SQL concepts like types of joins/union of data etc. Read data from a DB and write it back to a database Working of macros to avoid repetition of task, and enabling schedulers to run work flow(s) Design and develop ETL workflows and datasets in Knime to be used by the BI Reporting tool Perform end to end Data validation and prepare technical specifications and documentation for Knime workflows supporting BI reports. Develop and maintain interactive dashboards and reports using PowerBI to support data-driven decision-making. Lead and manage data analytics projects utilizing PowerBI, Python, and SQL to guide & deliver actionable business insights. Be able to succinctly visualize the findings through a PPT, a BI dashboard (Tableau, Qlikview, etc.) and highlight the key takeaways from a business perspective Ideal Candidate 4-7 years of relevant advanced analytics experience in Marketing, CRM, Pricing in either Retail, or CPG industries. Other B2C domains can be considered Experience in managing, cleaning and analyzing large datasets using tools like Python, R or SAS Experience in using multiple advanced analytics techniques or machine learning algorithms Experience in handling client calls and working independently with clients Understanding of consumer businesses such as Retail, CPG or Telecom Knowledge of working across multiple data types and files like flat files, RDBMS files; Knime workflows, Knime server, and multiple data platforms (SQL Server, Teradata, Hadoop, Spark); on premise or on the cloud Basic knowledge of advanced statistical techniques like Decision trees, different types of regressions, clustering, Forecasting (ARIMA/X), ML, etc. Other Skills Excellent communication skills (both written and oral) Ability to create client ready deliverables in Excel and PowerPoint Optimization techniques (linear, non-linear), and knowledge of supply chain VBA, Excel Macro programming, Tableau, QlikView Education Engineers from top tier institutes (IITs, DCE/NSIT, NITs) or Post Graduates in Maths/Statistics/OR from top Tier Colleges/Universities MBA from top tier B-schools In interested, please share your updated CV on kiran.meghani@wns.com or apply on https://smrtr.io/sz4-S Looking for immediate OR early joiners