629 Xgboost 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 Analyst, Inclusive Innovation & Analytics, Center for Inclusive Growth 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. The Center for Inclusive Growth is the social impact hub at Mastercard. The organization seeks to ensure that the benefits of an expanding economy accrue to all segments of society. Through actionable research, impact data science, programmatic grants, stakeholder engagement and global partnerships, the Center advances equitable and sustainable economic growth and financial inclusion around the world. The Center’s work is at the heart of Mastercard’s objective to be a force for good in the world. Reporting to Vice President, Inclusive Innovation & Analytics, the Analyst, will 1) create and/or scale data, data science, and AI solutions, methodologies, products, and tools to advance inclusive growth and the field of impact data science, 2) work on the execution and implementation of key priorities to advance external and internal data for social strategies, and 3) manage the operations to ensure operational excellence across the Inclusive Innovation & Analytics team. Key Responsibilities Data Analysis & Insight Generation Design, develop, and scale data science and AI solutions, tools, and methodologies to support inclusive growth and impact data science. Analyze structured and unstructured datasets to uncover trends, patterns, and actionable insights related to economic inclusion, public policy, and social equity. Translate analytical findings into insights through compelling visualizations and dashboards that inform policy, program design, and strategic decision-making. Create dashboards, reports, and visualizations that communicate findings to both technical and non-technical audiences. Provide data-driven support for convenings involving philanthropy, government, private sector, and civil society partners. Data Integration & Operationalization Assist in building and maintaining data pipelines for ingesting and processing diverse data sources (e.g., open data, text, survey data). Ensure data quality, consistency, and compliance with privacy and ethical standards. Collaborate with data engineers and AI developers to support backend infrastructure and model deployment. Team Operations Manage team operations, meeting agendas, project management, and strategic follow-ups to ensure alignment with organizational goals. Lead internal reporting processes, including the preparation of dashboards, performance metrics, and impact reports. Support team budgeting, financial tracking, and process optimization. Support grantees and grants management as needed Develop briefs, talking points, and presentation materials for leadership and external engagements. Translate strategic objectives into actionable data initiatives and track progress against milestones. Coordinate key activities and priorities in the portfolio, working across teams at the Center and the business as applicable to facilitate collaboration and information sharing Support the revamp of the Measurement, Evaluation, and Learning frameworks and workstreams at the Center Provide administrative support as needed Manage ad-hoc projects, events organization Qualifications Bachelor’s degree in Data Science, Statistics, Computer Science, Public Policy, or a related field. 2–4 years of experience in data analysis, preferably in a mission-driven or interdisciplinary setting. Strong proficiency in Python and SQL; experience with data visualization tools (e.g., Tableau, Power BI, Looker, Plotly, Seaborn, D3.js). Familiarity with unstructured data processing and robust machine learning concepts. Excellent communication skills and ability to work across technical and non-technical teams. Technical Skills & Tools Data Wrangling & Processing Data cleaning, transformation, and normalization techniques Pandas, NumPy, Dask, Polars Regular expressions, JSON/XML parsing, web scraping (e.g., BeautifulSoup, Scrapy) Machine Learning & Modeling Scikit-learn, XGBoost, LightGBM Proficiency in supervised/unsupervised learning, clustering, classification, regression Familiarity with LLM workflows and tools like Hugging Face Transformers, LangChain (a plus) Visualization & Reporting Power BI, Tableau, Looker Python libraries: Matplotlib, Seaborn, Plotly, Altair Dashboarding tools: Streamlit, Dash Storytelling with data and stakeholder-ready reporting Cloud & Collaboration Tools Google Cloud Platform (BigQuery, Vertex AI), Microsoft Azure Git/GitHub, Jupyter Notebooks, VS Code Experience with APIs and data integration tools (e.g., Airflow, dbt) Ideal Candidate You are a curious and collaborative analyst who believes in the power of data to drive social change. You’re excited to work with cutting-edge tools while staying grounded in the real-world needs of communities and stakeholders. 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 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.

Job Description: We're seeking a skilled and motivated ML/AI Engineer to join our team and drive end-to-end AI development for cutting-edge healthcare prediction models. As part of our AI delivery team you will be working on designing, developing, and deploying ML models to solve complex business challenges. Key Responsibilities: Design, develop, and deploy scalable machine learning models and AI solutions. Collaborate with engineers and product managers to understand business requirements and translate them into technical solutions. Analyse and preprocess large datasets for training and testing ML models. Experiment with different ML algorithms and techniques to improve model performance. Skills & Qualifications: Experience: B.Tech with 2-5 years of relevant experience in Machine Learning, AI, or Data Science roles. OR M.Tech, M. Statistics with 2-4 years of relevant experiencein Machine Learning, AI, or Data Science roles. Education: Bachelor's/master's degree in computer science or Statistics or any other relevant engineering / AI course from a Tier 1 or Tier 2 college. Technical Skills: Proficiency in programming languages such asPython & R Strong knowledge of classicalmachine learning algorithms with hands on experience in the following: Supervised (Classification model, regressions models) Unsupervised, (Clustering Algorithms, Autoencoders) Ensemble Models (Stacking, Bagging, Boosting techniques, Random Forest, XGBoost) Experience in data preprocessing, feature engineering, and handling large-scale datasets. Model evaluation techniques like accuracy, precision, recall, F1 score, AUC-ROC for classification, and MAE, MSE, RMSE, R-squared for regression. Explainable AI (XAI) techniques include methods like SHAP values, LIME, feature importance from decision trees, and partial dependence plots. Experience withML frameworkslikeTensorFlow, PyTorch, Scikit-learn,orKeras. Building & deploying Model APIs using framework like Flask, Fast API, Django, TensorFlow Serving etc. Knowledge ofcloud platformslike Azure (preferred), AWS, GCP and experience deploying models in such environments -> changed the wording, added points. Nice to Have: Object Oriented Programming. Familiarity withNLP, ortime seriesanalysis. -> Moving this into Nice to have, not bare min Exposure todeep learningmodels (RNN, LSTM) and working with GPUs.

Job Title: Senior Machine Learning Engineer We also recognize the importance of closing the 4-million-person cybersecurity talent gap. We aim to create a home for anyone seeking a meaningful future in cybersecurity and look for candidates across industries to join us in soulful work. More at . Role Overview: We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative Data Science and Engineering team. Reporting to the Data Science Director, you will play a critical role in building and scaling machine learning systems that power our cybersecurity products. You will work closely with data scientists and software engineers to design, develop, and deploy end-to-end ML pipelines, ensuring high performance and reliability in production. Your engineering expertise will directly contribute to solving complex challenges in areas such as threat detection, malware analysis, anomaly detection, and automated model workflows. About the role: As a Senior Machine Learning Engineer, you will be part of a high-impact team reporting to the Director of Data Science, focused on developing scalable, production-grade machine learning solutions to power cybersecurity products. Collaborate with data scientists and engineering teams to build and scale machine learning pipelines. Develop and deploy production-ready ML systems for use cases such as:Threat and attack detection,Threat hunting,Malware detection,Anomaly detection Build and optimize distributed data pipelines using Apache Spark and Python. Design and implement MLOps workflows including data preprocessing, model training, evaluation, and deployment. Monitor and retrain ML models based on feedback and performance in production. Develop model serving infrastructure for high availability, low latency, and scalability. Automate and streamline feature engineering, hyperparameter tuning, and CI/CD pipelines for ML models. Ensure model integration into security products with adherence to compliance and data governance standards. About you: You are an experienced ML Engineer with a strong foundation in software engineering and a passion for solving complex problems in the cybersecurity domain. Must-Have Qualifications: A Master Degree or Equivalent degree in Machine Learning, Computer Science, or Electrical Engineering, with Mathematics/Statistics at undergraduate level 4-6 years of industry experience as a Machine Learning Engineer Advanced proficiency in Python and strong programming fundamentals Hands-on experience with Apache Spark or PySpark for distributed data processing Solid understanding of machine learning concepts and experience with ML libraries like scikit-learn, XGBoost, TensorFlow, or PyTorch. Experience in building, deploying, and monitoring end-to-end ML systems in production Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker Pipelines). Proficiency in SQL and handling large-scale data Experience working with public cloud platforms (AWS, GCP, or Azure). Strong software engineering practices: Git, containerisation (Docker), testing, CI/CD Good to Have: Knowledge of Large Language Models (LLMs) such as GPT, BERT, LLaMA, or Falcon. Experience with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG)

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!

The ideal candidate for this position should have at least 6+ years of experience in Machine Learning, with a primary focus on Google Vertex AI and Python. You must possess a strong understanding of MLOps practices and hands-on experience in deploying and productionizing ML models. Proficiency in Python is a must, along with experience working with Google Vertex AI. Additionally, solid knowledge of machine learning algorithms such as XGBoost, Classification models, and BigQuery ML (BQML) is required. As a member of the team, your key responsibilities will include designing, building, and maintaining ML infrastructure on Google Cloud Platform (GCP) using tools like Vertex AI, GKE, Dataflow, BigQuery, and Cloud Functions. You will be responsible for developing and automating ML pipelines for model training, validation, deployment, and monitoring using tools like Kubeflow Pipelines, TFX, or Vertex AI Pipelines. Collaboration with Data Scientists to productionize ML models and support experimentation workflows will be essential. You will also be expected to implement model monitoring and alerting for drift, performance degradation, and data quality issues, along with managing and scaling containerized ML workloads using Kubernetes (GKE) and Docker. Setting up CI/CD workflows for ML using tools like Cloud Build, Bitbucket, Jenkins, or similar will be part of your daily tasks. Ensuring proper security, versioning, and compliance across the ML lifecycle is crucial, as well as maintaining documentation, artifacts, and reusable templates for reproducibility and auditability. Having a GCP MLE Certification will be considered a plus. This is a full-time, permanent position with the possibility of remote work. The job location is Hyderabad, and the work schedule includes day and morning shifts. Application Questions: - Do you have hands-on experience in deploying and productionizing ML models - Are you proficient in Python - Do you have experience with Google Vertex AI - Do you have solid knowledge of machine learning algorithms such as XGBoost, Classification models, BigQuery ML (BQML) If you meet the qualifications and are looking for a challenging opportunity in the field of Machine Learning, we encourage you to apply for this position.,

You are a strategic thinker passionate about driving solutions in financial analysis. You have found the right team. As a Quant Analytics Analyst within the Analytics Team, you will leverage your expertise in tools like SAS, SQL, Python, and Alteryx to deliver complex analytical projects. You will build statistical models, deploy them, and generate impactful insights with measurable P&L impact. You will collaborate with finance, marketing, technology, and business teams to present clear and concise results and recommendations. Experience in retail finance or Credit card finance within a bank is a big plus. You will perform detailed quantitative analysis and data deep dive to answer questions pertaining to key business objectives. You will create and maintain dashboards to track key business P&L metrics. Providing informative business financial information and coordinating business financial planning and budget management will be part of your responsibilities. Partnering effectively with finance, marketing, technology, and business teams is crucial. You will present results and recommendations clearly and concisely. Required qualifications, capabilities, and skills include excellent knowledge of SQL and the ability to write complex SQL queries. Experience in using data extraction and data analysis tools like SQL/Pyspark SQL/Alteryx/Python/SAS is necessary. A minimum of 3 years of experience working on analytical projects involving product analysis and statistical modeling is required. Good knowledge of statistical modeling techniques related to time series forecasting, regression (linear/logistic), ML models like XGBoost, and NLP is essential. Experience in building analytical dashboards using tools like Tableau, Quicksight, SAS Visual Analytics, Streamlit, etc., is preferred. Excellent communication (verbal and written) skills, proficiency in Microsoft Office (especially Excel), and a basic understanding of cloud ops on AWS are necessary. Preferred qualifications, capabilities, and skills include a Bachelor's degree in Engineering, with CFA/FRM/MBA (Finance) being an advantage but not mandatory.,

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.,

Job Description You are a strategic thinker passionate about driving solutions in financial analysis. You have found the right team. As a Quant Analytics Analyst within the Analytics Team, you will leverage your expertise in tools like SAS, SQL, Python, and Alteryx to deliver complex analytical projects. You will build statistical models, deploy them, and generate impactful insights with measurable P&L impact. You will collaborate with finance, marketing, technology, and business teams to present clear and concise results and recommendations. Job Responsibilities Experience in retail finance or Credit card finance within a bank a big plus Perform detailed quantitative analysis and data deep dive to answer questions pertaining to key business objectives Create and maintain dashboard to track key business p&l metrics Provide informative business financial information and coordinate business financial planning and budget management Partner effectively with finance, marketing and technology and business teams Present results and recommendations clearly and concisely Required Qualifications, Capabilities, And Skills Excellent knowledge of SQL and able to write complex sql queries. Experience in using Data extraction and Data analysis tools like SQL/Pyspark Sql/ Alteryx /Python/SAS Minimum 3 years’ experience working on analytical projects involving product analysis and statistical modeling Good knowledge of statistical modeling techniques related to time series forecasting, regression(line/logistic), ML model like XGBoost and NLP Have experience in building analytical dashboards using tools like Tableau, Quicksight, SAS Visual analytics, streamlit etc. Excellent communication (verbal and written) skills Proficiency in Microsoft Office (especially Excel) Basic understanding of cloud ops on AWS Preferred Qualifications, Capabilities, And Skills Bachelor’s degree in Engineering required, CFA/FRM/ MBA (Finance) an advantage but not mandatory ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

🧠 Job Title: Senior Machine Learning Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 4–8 years Education : B.Tech / M.Tech / Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related fields 🚀 About Darwix AI Darwix AI is India's fastest-growing GenAI SaaS startup, building real-time conversational intelligence and agent-assist platforms that supercharge omnichannel enterprise sales teams across India, MENA, and Southeast Asia. Our mission is to redefine how revenue teams operate by using Generative AI, LLMs, Voice AI , and deep analytics to deliver better conversations, faster deal cycles, and consistent growth. Our flagship platform, Transform+ , analyzes millions of hours of sales conversations, gives live nudges, builds AI-powered sales content, and enables revenue teams to become truly data-driven — in real time. We’re backed by marquee investors, industry veterans, and AI experts, and we’re expanding fast. As a Senior Machine Learning Engineer , you will play a pivotal role in designing and deploying intelligent ML systems that power every layer of this platform — from speech-to-text, diarization, vector search, and summarization to recommendation engines and personalized insights. 🎯 Role Overview This is a high-impact, high-ownership role for someone who lives and breathes data, models, and real-world machine learning. You will design, train, fine-tune, deploy, and optimize ML models across various domains — speech, NLP, tabular, and ranking. Your work will directly power critical product features: from personalized agent nudges and conversation scoring to lead scoring, smart recommendations, and retrieval-augmented generation (RAG) pipelines. You’ll be the bridge between data science, engineering, and product — converting ideas into models, and models into production-scale systems with tangible business value. 🧪 Key Responsibilities🔬 1. Model Design, Training, and Optimization Develop and fine-tune machine learning models using structured, unstructured, and semi-structured data sources. Work with models across domains: text classification, speech transcription, named entity recognition, topic modeling, summarization, time series, and recommendation systems. Explore and implement transformer architectures, BERT-style encoders, Siamese networks, and retrieval-based models. 📊 2. Data Engineering & Feature Extraction Build robust ETL pipelines to clean, label, and enrich data for supervised and unsupervised learning tasks. Work with multimodal inputs — audio, text, metadata — and build smart representations for downstream tasks. Automate data collection from APIs, CRMs, sales transcripts, and call logs. ⚙️ 3. Productionizing ML Pipelines Package and deploy models in scalable APIs (using FastAPI, Flask, or similar frameworks). Work closely with DevOps to containerize and orchestrate ML workflows using Docker, Kubernetes, or CI/CD pipelines. Ensure production readiness: logging, monitoring, rollback, and fail-safes. 📈 4. Experimentation & Evaluation Design rigorous experiments using A/B tests, offline metrics, and post-deployment feedback loops. Continuously optimize model performance (latency, accuracy, precision-recall trade-offs). Implement drift detection and re-training pipelines for models in production. 🔁 5. Collaboration with Product & Engineering Translate business problems into ML problems and align modeling goals with user outcomes. Partner with product managers, AI researchers, data annotators, and frontend/backend engineers to build and launch features. Contribute to the product roadmap with ML-driven ideas and prototypes. 🛠️ 6. Innovation & Technical Leadership Evaluate open-source and proprietary LLM APIs, AutoML frameworks, vector databases, and model inference techniques. Drive innovation in voice-to-insight systems (ASR + Diarization + NLP). Mentor junior engineers and contribute to best practices in ML development and deployment. 🧰 Tech Stack🔧 Languages & Frameworks Python (core), SQL, Bash PyTorch, TensorFlow, HuggingFace, scikit-learn, XGBoost, LightGBM 🧠 ML & AI Ecosystem Transformers, RNNs, CNNs, CRFs BERT, RoBERTa, GPT-style models OpenAI API, Cohere, LLaMA, Mistral, Anthropic Claude FAISS, Pinecone, Qdrant, LlamaIndex ☁️ Deployment & Infrastructure Docker, Kubernetes, GitHub Actions, Jenkins AWS (EC2, Lambda, S3, SageMaker), GCP, Azure Redis, PostgreSQL, MongoDB 📊 Monitoring & Experimentation MLflow, Weights & Biases, TensorBoard, Prometheus, Grafana 👨‍💼 Qualifications🎓 Education Bachelor’s or Master’s degree in CS, AI, Statistics, or related quantitative disciplines. Certifications in advanced ML, data science, or AI are a plus. 🧑‍💻 Experience 4–8 years of hands-on experience in applied machine learning. Demonstrated success in deploying models to production at scale. Deep familiarity with transformer-based architectures and model evaluation. ✅ You’ll Excel In This Role If You… Thrive on solving end-to-end ML problems — not just notebooks, but deployment, testing, and iteration. Obsess over clean, maintainable, reusable code and pipelines. Think from first principles and challenge model assumptions when they don’t work. Are deeply curious and have built multiple projects just because you wanted to know how something works. Are comfortable working with ambiguity, fast timelines, and real-time data challenges. Want to build AI products that get used by real people and drive revenue outcomes — not just vanity demos. 💼 What You’ll Get at Darwix AI Work with some of the brightest minds in AI , product, and design. Solve AI problems that push the boundaries of real-time, voice-first, multilingual enterprise use cases. Direct mentorship from senior architects and AI scientists. Competitive compensation (₹30L–₹45L CTC) + ESOPs + rapid growth trajectory. Opportunity to shape the future of a global-first AI startup built from India. Hands-on experience with the most advanced tech stack in applied ML and production AI. Front-row seat to a generational company that is redefining enterprise AI. 📩 How to Apply Ready to build with us? Send your resume, GitHub/portfolio, and a short write-up on: “What’s the most interesting ML system you’ve built — and what made it work?” Email: people@darwix.ai Subject: Senior ML Engineer – Application 🔐 Final Notes We value speed, honesty, and humility. We ship fast, fail fast, and learn even faster. This role is designed for high-agency, hands-on ML engineers who want to make a difference — not just write code. If you’re looking for a role where you own real impact , push technical boundaries, and work with a team that’s as obsessed with AI as you are — then Darwix AI is the place for you. Darwix AI – GenAI for Revenue Teams. Built from India, for the World.

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Purpose of the role This role sits at the intersection of data science and revenue growth strategy, focused on developing advanced analytical solutions to optimize pricing, trade promotions, and product mix. The candidate will lead the end-to-end design, deployment, and automation of machine learning models and statistical frameworks that support commercial decision-making, predictive scenario planning, and real-time performance tracking. By leveraging internal and external data sources—including transactional, market, and customer-level data—this role will deliver insights into price elasticity, promotional lift, channel efficiency, and category dynamics. The goal is to drive measurable improvements in gross margin, ROI on trade spend, and volume growth through data-informed strategies. Key tasks & accountabilities Design and implement price elasticity models using linear regression, log-log models, and hierarchical Bayesian frameworks to understand consumer response to pricing changes across channels and segments. Build uplift models (e.g., Linear Regression, XGBoost for treatment effect) to evaluate promotional effectiveness and isolate true incremental sales vs. base volume. Develop demand forecasting models using ARIMA, SARIMAX, and Prophet, integrating external factors such as seasonality, promotions, and competitor activity, time-series clustering and k-means segmentation to group SKUs, customers, and geographies for targeted pricing and promotion strategies. Construct assortment optimization models using conjoint analysis, choice modeling, and market basket analysis to support category planning and shelf optimization. Use Monte Carlo simulations and what-if scenario modeling to assess revenue impact under varying pricing, promo, and mix conditions. Conduct hypothesis testing (t-tests, ANOVA, chi-square) to evaluate statistical significance of pricing and promotional changes. Create LTV (lifetime value) and customer churn models to prioritize trade investment decisions and drive customer retention strategies. Integrate Nielsen, IRI, and internal POS data to build unified datasets for modeling and advanced analytics in SQL, Python (pandas, statsmodels, scikit-learn), and Azure Databricks environments. Automate reporting processes and real-time dashboards for price pack architecture (PPA), promotion performance tracking, and margin simulation using advanced Excel and Python. Lead post-event analytics using pre/post experimental designs, including difference-in-differences (DiD) methods to evaluate business interventions. Collaborate with Revenue Management, Finance, and Sales leaders to convert insights into pricing corridors, discount policies, and promotional guardrails. Translate complex statistical outputs into clear, executive-ready insights with actionable recommendations for business impact. Continuously refine model performance through feature engineering, model validation, and hyperparameter tuning to ensure accuracy and scalability. Provide mentorship to junior analysts, enhancing their skills in modeling, statistics, and commercial storytelling. Maintain documentation of model assumptions, business rules, and statistical parameters to ensure transparency and reproducibility. Other Competencies Required Presentation Skills: Effectively presenting findings and insights to stakeholders and senior leadership to drive informed decision-making. Collaboration: Working closely with cross-functional teams, including marketing, sales, and product development, to implement insights-driven strategies. Continuous Improvement: Actively seeking opportunities to enhance reporting processes and insights generation to maintain relevance and impact in a dynamic market environment. Data Scope Management: Managing the scope of data analysis, ensuring it aligns with the business objectives and insights goals. Act as a steadfast advisor to leadership, offering expert guidance on harnessing data to drive business outcomes and optimize customer experience initiatives. Serve as a catalyst for change by advocating for data-driven decision-making and cultivating a culture of continuous improvement rooted in insights gleaned from analysis. Continuously evaluate and refine reporting processes to ensure the delivery of timely, relevant, and impactful insights to leadership stakeholders while fostering an environment of ownership, collaboration, and mentorship within the team. Business Environment Main Characteristics: Work closely with Zone Revenue Management teams. Work in a fast-paced environment. Provide proactive communication to the stakeholders. This is an offshore role and requires comfort with working in a virtual environment. GCC is referred to as the offshore location. The role requires working in a collaborative manner with Zone/country business heads and GCC commercial teams. Summarize insights and recommendations to be presented back to the business. Continuously improve, automate, and optimize the process. Geographical Scope: Europe Qualifications, Experience, Skills Level of educational attainment required: Bachelor or Post-Graduate in the field of Business & Marketing, Engineering/Solution, or other equivalent degree or equivalent work experience. MBA/Engg. in a relevant technical field such as Marketing/Finance. Extensive experience solving business problems using quantitative approaches. Comfort with extracting, manipulating, and analyzing complex, high volume, high dimensionality data from varying sources. Previous Work Experience Required 5-8 years of experience in the Retail/CPG domain. Technical Skills Required Data Manipulation & Analysis: Advanced proficiency in SQL, Python (Pandas, NumPy), and Excel for structured data processing. Data Visualization: Expertise in Power BI and Tableau for building interactive dashboards and performance tracking tools. Modeling & Analytics: Hands-on experience with regression analysis, time series forecasting, and ML models using scikit-learn or XGBoost. Data Engineering Fundamentals: Knowledge of data pipelines, ETL processes, and integration of internal/external datasets for analytical readiness. Proficient in Python (pandas, scikit-learn, statsmodels), SQL, and Power BI. Skilled in regression, Bayesian modeling, uplift modeling, time-series forecasting (ARIMA, SARIMAX, Prophet), and clustering (k-means). Strong grasp of hypothesis testing, model validation, and scenario simulation. And above all of this, an undying love for beer! We dream big to create future with more cheers .

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Purpose of the role This role sits at the intersection of data science and revenue growth strategy, focused on developing advanced analytical solutions to optimize pricing, trade promotions, and product mix. The candidate will lead the end-to-end design, deployment, and automation of machine learning models and statistical frameworks that support commercial decision-making, predictive scenario planning, and real-time performance tracking. By leveraging internal and external data sources—including transactional, market, and customer-level data—this role will deliver insights into price elasticity, promotional lift, channel efficiency, and category dynamics. The goal is to drive measurable improvements in gross margin, ROI on trade spend, and volume growth through data-informed strategies. Key tasks & accountabilities Design and implement price elasticity models using linear regression, log-log models, and hierarchical Bayesian frameworks to understand consumer response to pricing changes across channels and segments. Build uplift models (e.g., Linear Regression, XGBoost for treatment effect) to evaluate promotional effectiveness and isolate true incremental sales vs. base volume. Develop demand forecasting models using ARIMA, SARIMAX, and Prophet, integrating external factors such as seasonality, promotions, and competitor activity, time-series clustering and k-means segmentation to group SKUs, customers, and geographies for targeted pricing and promotion strategies. Construct assortment optimization models using conjoint analysis, choice modeling, and market basket analysis to support category planning and shelf optimization. Use Monte Carlo simulations and what-if scenario modeling to assess revenue impact under varying pricing, promo, and mix conditions. Conduct hypothesis testing (t-tests, ANOVA, chi-square) to evaluate statistical significance of pricing and promotional changes. Create LTV (lifetime value) and customer churn models to prioritize trade investment decisions and drive customer retention strategies. Integrate Nielsen, IRI, and internal POS data to build unified datasets for modeling and advanced analytics in SQL, Python (pandas, statsmodels, scikit-learn), and Azure Databricks environments. Automate reporting processes and real-time dashboards for price pack architecture (PPA), promotion performance tracking, and margin simulation using advanced Excel and Python. Lead post-event analytics using pre/post experimental designs, including difference-in-differences (DiD) methods to evaluate business interventions. Collaborate with Revenue Management, Finance, and Sales leaders to convert insights into pricing corridors, discount policies, and promotional guardrails. Translate complex statistical outputs into clear, executive-ready insights with actionable recommendations for business impact. Continuously refine model performance through feature engineering, model validation, and hyperparameter tuning to ensure accuracy and scalability. Provide mentorship to junior analysts, enhancing their skills in modeling, statistics, and commercial storytelling. Maintain documentation of model assumptions, business rules, and statistical parameters to ensure transparency and reproducibility. Other Competencies Required Presentation Skills: Effectively presenting findings and insights to stakeholders and senior leadership to drive informed decision-making. Collaboration: Working closely with cross-functional teams, including marketing, sales, and product development, to implement insights-driven strategies. Continuous Improvement: Actively seeking opportunities to enhance reporting processes and insights generation to maintain relevance and impact in a dynamic market environment. Data Scope Management: Managing the scope of data analysis, ensuring it aligns with the business objectives and insights goals. Act as a steadfast advisor to leadership, offering expert guidance on harnessing data to drive business outcomes and optimize customer experience initiatives. Serve as a catalyst for change by advocating for data-driven decision-making and cultivating a culture of continuous improvement rooted in insights gleaned from analysis. Continuously evaluate and refine reporting processes to ensure the delivery of timely, relevant, and impactful insights to leadership stakeholders while fostering an environment of ownership, collaboration, and mentorship within the team. Business Environment Main Characteristics: Work closely with Zone Revenue Management teams. Work in a fast-paced environment. Provide proactive communication to the stakeholders. This is an offshore role and requires comfort with working in a virtual environment. GCC is referred to as the offshore location. The role requires working in a collaborative manner with Zone/country business heads and GCC commercial teams. Summarize insights and recommendations to be presented back to the business. Continuously improve, automate, and optimize the process. Geographical Scope: Europe 3. Qualifications, Experience, Skills Level of educational attainment required: Bachelor or Post-Graduate in the field of Business & Marketing, Engineering/Solution, or other equivalent degree or equivalent work experience. MBA/Engg. in a relevant technical field such as Marketing/Finance. Extensive experience solving business problems using quantitative approaches. Comfort with extracting, manipulating, and analyzing complex, high volume, high dimensionality data from varying sources. Previous Work Experience Required 5-8 years of experience in the Retail/CPG domain. Technical Skills Required Data Manipulation & Analysis: Advanced proficiency in SQL, Python (Pandas, NumPy), and Excel for structured data processing. Data Visualization: Expertise in Power BI and Tableau for building interactive dashboards and performance tracking tools. Modeling & Analytics: Hands-on experience with regression analysis, time series forecasting, and ML models using scikit-learn or XGBoost. Data Engineering Fundamentals: Knowledge of data pipelines, ETL processes, and integration of internal/external datasets for analytical readiness. Proficient in Python (pandas, scikit-learn, statsmodels), SQL, and Power BI. Skilled in regression, Bayesian modeling, uplift modeling, time-series forecasting (ARIMA, SARIMAX, Prophet), and clustering (k-means). Strong grasp of hypothesis testing, model validation, and scenario simulation. And above all of this, an undying love for beer! We dream big to create future with more cheers .

We use cookies to offer you the best possible website experience. Your cookie preferences will be stored in your browser’s local storage. This includes cookies necessary for the website's operation. Additionally, you can freely decide and change any time whether you accept cookies or choose to opt out of cookies to improve website's performance, as well as cookies used to display content tailored to your interests. Your experience of the site and the services we are able to offer may be impacted if you do not accept all cookies. Press Tab to Move to Skip to Content Link Skip to main content Home Page Home Page Life At YASH Core Values Careers Business Consulting Jobs Digital Jobs ERP IT Infrastructure Jobs Sales & Marketing Jobs Software Development Jobs Solution Architects Jobs Join Our Talent Community Social Media LinkedIn Twitter Instagram Facebook Search by Keyword Search by Location Home Page Home Page Life At YASH Core Values Careers Business Consulting Jobs Digital Jobs ERP IT Infrastructure Jobs Sales & Marketing Jobs Software Development Jobs Solution Architects Jobs Join Our Talent Community Social Media LinkedIn Twitter Instagram Facebook View Profile Employee Login Search by Keyword Search by Location Show More Options Loading... Requisition ID All Skills All Select How Often (in Days) To Receive An Alert: Create Alert Select How Often (in Days) To Receive An Alert: Apply now » Apply Now Start apply with LinkedIn Please wait... Lead Data Scientist - AI/ML Job Date: Jul 25, 2025 Job Requisition Id: 60916 Location: Hyderabad, TG, IN Pune, IN Pune, MH, IN Indore, MP, IN YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future. We are looking forward to hire AI/ML Professionals in the following areas : Designation: Lead Data Scientist We are seeking a highly motivated and experienced Lead Data Scientist to join our growing team. In this role, you will be responsible for leading complex data science projects, mentoring junior data scientists, and driving the development of innovative solutions that leverage data to achieve business objectives. You will apply your deep expertise in machine learning, statistical modeling, and data analysis to extract actionable insights and drive strategic decision-making. Experience: 8–11 Years Job Type: Full-time Responsibilities: End-to-end delivery ownership of ML and GenAI use cases. Architect RAG pipelines and build enterprise-scale GenAI accelerators. Collaborate with architects and presales teams. Ensure code modularity, testability, and governance. Required Skills: LangChain, LangGraph, embedding techniques, prompt engineering. Classical ML: XGBoost, Random Forest, time-series forecasting. Knowledge of Python ML stack and FastAPI. Strong understanding of security and cloud optimization. At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale. Our Hyperlearning workplace is grounded upon four principles Flexible work arrangements, Free spirit, and emotional positivity Agile self-determination, trust, transparency, and open collaboration All Support needed for the realization of business goals, Stable employment with a great atmosphere and ethical corporate culture Apply now » Apply Now Start apply with LinkedIn Please wait... Find Similar Jobs: Careers Home View All Jobs Top Jobs Quick Links Blogs Events Webinars Media Contact Contact Us Copyright © 2020. YASH Technologies. All Rights Reserved.

As a Jr. Software Engineer (AI ML) at SynapseIndia, you will have the opportunity to work with cutting-edge technologies and contribute to the development of innovative solutions. With a focus on AI/ML, you will play a crucial role in designing, developing, and deploying machine learning models and AI algorithms using Python and relevant libraries. To excel in this role, you should hold a Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a related field. Additionally, having 0-2 years of professional experience in Python programming with a specialization in AI/ML is essential. Your strong experience with Python ML libraries such as scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, along with a solid understanding of machine learning algorithms, neural networks, and deep learning will be highly valuable. Furthermore, your proficiency in data manipulation libraries such as Pandas, NumPy, and data visualization tools like Matplotlib, Seaborn, as well as experience with cloud platforms like AWS, GCP, Azure, and deploying ML models using Docker, Kubernetes will be beneficial. Any familiarity with NLP, Computer Vision, or other AI domains will be considered a plus. Your responsibilities will include collaborating with cross-functional teams to gather requirements and translate business problems into AI/ML solutions. You will be optimizing and scaling machine learning pipelines and systems for production, performing data preprocessing, feature engineering, and exploratory data analysis, and implementing and fine-tuning deep learning models using frameworks like TensorFlow, PyTorch, or similar. Additionally, you will be expected to conduct experiments, evaluate model performance using statistical methods, write clean, maintainable, and well-documented code, mentor junior developers, participate in code reviews, and stay up-to-date with the latest AI/ML research and technologies. Ensuring seamless model deployment and integration with existing infrastructure will also be part of your role. If you are a proactive individual with strong problem-solving skills, the ability to work independently and collaboratively, excellent communication skills, and familiarity with REST APIs, microservices architecture, version control systems like Git, MLOps best practices and tools, distributed computing, and big data tools like Spark or Hadoop, we encourage you to apply for this exciting opportunity at SynapseIndia. Join us and be a part of our dynamic team where your contributions are recognized and rewarded, and where you can grow both personally and professionally in a structured, eco-friendly workplace that prioritizes the well-being and job security of its employees.,

Company Description WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees. Job Description Job Overview: Responsible for leading data science initiatives, developing advanced analytics models and ensuring successful execution of data-driven projects for clients in the retail. Will work closely with key client stakeholders to understand their business challenges and leverage data science to deliver actionable insights that drive business growth and efficiency. Lead the design, development and implementation of advanced analytics models. Including predictive and prescriptive models for retail clients.Should be able to convert mathematical/ statistics-based research into sustainable data science solutions Candidate should be able to think from first principles to define & evangelize solutions for any client business problem Leverage deep knowledge of the retail to develop data-driven solutions that address industry-specific challenges. Apply AI/ML statistical methods to solve complex business problems and determine new opportunities for clients. Ensure project delivery of high-quality, actionable insights that drive business decisions and outcomes. Ensure end-to-end lifecycle (scoping to Delivery) of data science projects. Collaborate with cross-functional teams to ensure seamless project execution.Manage timelines, resources, and deliverables to meet client expectations and project goals. Drive innovation by exploring new data science techniques, tools, and technologies that can enhance the value delivered to clients. Strong hands-on experience with data science tools and technologies (e.g., Python, R, SQL, machine learning frameworks). Hand-on experience with a range of data science models including regression, classification, clustering, decision tree, random forest, support vector machine, naïve Bayes, GBM, XGBoost, multiple linear regression, logistic regression, and ARIMA/ARIMAX. Should be competent in Python (Pandas, NumPy, scikit-learn etc.), possess high levels of analytical skills and have experience in the creation and/or evaluation of predictive models. Preferred experience in areas such as time series analysis, market mix modelling, attribution modelling, churn modelling, market basket analysis, etc Good communication and project management skills. Should be able to communicate effectively to a wide range of audiences, both technical and business. Adept in creating Presentations, reports etc to present the analysis findings to key client stakeholders. Strong team management skills with a passion for mentoring and developing talent. Qualifications Educational Qualification:BTech/Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1-2 institutions Or BE/B-Tech, MCA or MBA

Role & responsibilities Job Title: Data Scientist (3-5 Years Experience) Key Responsibilities: Develop and implement machine learning and deep learning models for various business problems, with a strong focus on time series forecasting. Analyze large, complex datasets to extract actionable insights and identify trends, patterns, and opportunities for improvement. Design, build, and validate predictive models using state-of-the-art techniques, ensuring scalability and robustness. Collaborate with cross-functional teams (Product, Engineering, Business) to translate business requirements into data science solutions. Communicate findings and recommendations clearly to both technical and non-technical stakeholders. Stay updated with the latest research and advancements in machine learning, deep learning, and time series analysis, and proactively apply new techniques as appropriate. Mentor junior team members and contribute to a culture of continuous learning and innovation. Requirements Required Skills & Qualifications: 3-5 years of hands-on experience in data science, machine learning, and statistical modeling. Strong expertise in time series forecasting (ARIMA, XGBoost, RandomForest, TFT, NHITS, etc.) and familiarity with deep learning frameworks (TensorFlow, PyTorch). Excellent programming skills in Python (preferred), with proficiency in libraries such as NumPy, Pandas, scikit-learn, and visualization tools (Matplotlib, Seaborn, Plotly). Solid conceptual understanding of machine learning algorithms, deep learning architectures, and statistical methods. Experience with data preprocessing, feature engineering, and model evaluation. Ability to learn quickly and adapt to new technologies, tools, and methodologies. Strong problem-solving skills and a keen attention to detail. Excellent communication and presentation skills. Preferred Qualifications: Experience with cloud platforms and MLOps tools. Exposure to big data technologies (Spark, Hadoop) is a plus. Masters degree in Computer Science, Statistics, Mathematics, or a related field. Benefits What a Consulting role at Thoucentric will offer you? Opportunity to define your career path and not as enforced by a manager A great consulting environment with a chance to work with Fortune 500 companies and startups alike. A dynamic but relaxed and supportive working environment that encourages personal development. Be part of One Extended Family. We bond beyond work - sports, get-togethers, common interests etc. Work in a very enriching environment with Open Culture, Flat Organization and Excellent Peer Group. Be part of the exciting Growth Story of Thoucentric!

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation. At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future. We are looking forward to hire AI/ML Professionals in the following areas : Designation: Lead Data Scientist We are seeking a highly motivated and experienced Lead Data Scientist to join our growing team. In this role, you will be responsible for leading complex data science projects, mentoring junior data scientists, and driving the development of innovative solutions that leverage data to achieve business objectives. You will apply your deep expertise in machine learning, statistical modeling, and data analysis to extract actionable insights and drive strategic decision-making. Experience: 8–11 Years Job Type: Full-time Responsibilities End-to-end delivery ownership of ML and GenAI use cases. Architect RAG pipelines and build enterprise-scale GenAI accelerators. Collaborate with architects and presales teams. Ensure code modularity, testability, and governance. Required Skills LangChain, LangGraph, embedding techniques, prompt engineering. Classical ML: XGBoost, Random Forest, time-series forecasting. Knowledge of Python ML stack and FastAPI. Strong understanding of security and cloud optimization. At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale. Our Hyperlearning workplace is grounded upon four principles Flexible work arrangements, Free spirit, and emotional positivity Agile self-determination, trust, transparency, and open collaboration All Support needed for the realization of business goals, Stable employment with a great atmosphere and ethical corporate culture

Sanctity AI is a Netherlands-based startup founded by an IIT alum, specializing in ethical, safe, and impactful artificial intelligence. Our agile team is deeply focused on critical areas like AI alignment, responsible LLM training, prompt orchestration, and advanced agent infrastructure. In a landscape where many talk ethics, we build and deploy solutions that genuinely embody ethical AI principles. Sanctity AI is positioned at the forefront of solving real-world alignment challenges, shaping the future of trustworthy artificial intelligence. We leverage proprietary algorithms, rigorous ethical frameworks, and cutting-edge research to deliver AI solutions with unparalleled transparency, robustness, and societal impact. Sanctity AI represents a rare opportunity in the rapidly evolving AI ecosystem, committed to sustainable innovation and genuine human-AI harmony. The Role As an AI ML Intern reporting directly to the founder, you’ll go beyond just coding. You’ll own whole pipelines—from data wrangling to deploying cutting-edge ML models in production. You’ll also get hands-on experience with large language models (LLMs), prompt engineering, semantic search, and retrieval-augmented generation. Whether it’s spinning up APIs in FastAPI, containerizing solutions with Docker, or exploring vector and graph databases like Pinecone and Neo4j, you’ll be right at the heart of our AI innovation. What You’ll Tackle Data to Insights: Dive into heaps of raw data, and turn it into actionable insights that shape real decisions. Model Building & Deployment: Use Scikit-learn, XGBoost, LightGBM, and advanced deep learning frameworks (TensorFlow, PyTorch, Keras) to develop state-of-the-art models. Then, push them to production—scaling on AWS, GCP, or other cloud platforms. LLM & Prompt Engineering: Fine-tune and optimize large language models. Experiment with prompt strategies and incorporate RAG (Retrieval-Augmented Generation) for more insightful outputs. Vector & Graph Databases: Implement solutions using Pinecone, Neo4j, or similar technologies for advanced search and data relationships. Microservices & Big Data: Leverage FastAPI (or similar frameworks) to build robust APIs. If you love large-scale data processing, dabble in Apache Spark, Hadoop, or Kafka to handle the heavy lifting. Iterative Improvement: Observe model performance, gather metrics, and keep refining until the results shine. Who You Are Python Pro: You write clean, efficient Python code using libraries like Pandas, NumPy, and Scikit-learn. Passionate About AI/ML: You’ve got a solid grasp of algorithms and can’t wait to explore deep learning or advanced NLP. LLM Enthusiast: You’re familiar with training or fine-tuning large language models and love the challenge of prompt engineering. Cloud & Containers Savvy: You’ve at least toyed with AWS, GCP, or similar, and have some experience with Docker or other containerization tools. Data-Driven & Detail-Oriented: You enjoy unearthing insights in noisy datasets and take pride in well-documented, maintainable code. Curious & Ethical: You believe AI should be built responsibly and love learning about new ways to do it better. Languages: You can fluently communicate complex technical ideas in English. Fluency in Dutch, Spanish or French is a plus. Math Wizard: You have a strong grip on Advanced Mathematics and Statistical modeling. This is a core requirement. Why Join Us? Real-World Impact: Your work will address real world and industry challenges—problems that genuinely need AI solutions. Mentorship & Growth: Team up daily with founders and seasoned AI pros, accelerating your learning and skill-building. Experimentation Culture: We encourage big ideas and bold experimentation. Want to try a new approach? Do it. Leadership Path: Show us your passion and skills, and you could move into a core founding team member role, shaping our future trajectory. Interested? Send over your résumé, GitHub repos, or any project links that showcase your passion and talent. We can’t wait to see how you think, build, and innovate. Let’s team up to create AI that isn’t just powerful—but also responsibly built for everyone.

Red & White Education Pvt Ltd , founded in 2008, is Gujarat's leading educational institute. Accredited by NSDC and ISO, we focus on Integrity, Student-Centricity, Innovation, and Unity. Our goal is to equip students with industry-relevant skills and ensure they are employable globally. Join us for a successful career path. Job Description: Faculties guide students, deliver course materials, conduct lectures, assess performance, and provide mentorship. Strong communication skills and a commitment to supporting students are essential. Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. Additional Skills: Confident body language and clear communication. Strong classroom management and discipline skills. Punctual, prepared, and passionate about teaching. Open to learning and professional development. Proficient in verbal and written communication. Strong problem-solving, leadership, and decision-making abilities. Positive attitude and ability to work independently. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹40,000.00 per month Benefits: Cell phone reimbursement Flexible schedule Leave encashment Paid sick time Paid time off Schedule: Day shift Morning shift Supplemental Pay: Performance bonus Yearly bonus Application Question(s): Current Salary? Experience: Teaching / Mentoring: 1 year (Required) AI: 1 year (Required) ML: 1 year (Required) Data science: 1 year (Required) Location: Ahmedabad, Gujarat (Required) Work Location: In person

SynapseIndia is a software development company with over 24 years of experience, featuring development offices in India and the USA. We serve clients worldwide, delivering innovative solutions tailored to their needs. Our Noida SEZ office is conveniently located just a 10-minute walk from the nearest metro station. Why work with us? Partnerships with Industry Leaders: We are a Google and Microsoft partner, staffed by certified professionals. Global Presence: As a multinational corporation, we have clients and employees across the globe. Structured Environment: We follow CMMI Level-5 compliant processes to ensure quality and efficiency. Timely Salaries: We have consistently paid salaries on time since our inception. Job Stability: Despite market fluctuations, we have not had to lay off employees. Work-Life Balance: Enjoy weekends off on the 2nd and last Saturday of every month, with no night shifts. Our employees are 100% satisfied, thanks to a culture of trust and growth opportunities. Eco-Friendly Workplace: We promote health and well-being with special anti-radiation and energy removal features in our offices. We prioritize the job security of all our employees. We celebrate all festivals with enthusiasm and joy. Yearly Appraisals: Exceptional performers can receive over 100% increments during appraisals. We recognize and reward top performers on a monthly basis for their outstanding contributions. We provide Accidental and Medical Insurance to our employees. Who are we looking for? Designation : Jr. Software Engineer (AI ML) Experience Range : 0 to 2 years What is the work? Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field. 0-2 years of professional experience in Python programming with a focus on AI/ML. Strong experience with Python ML libraries such as scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, etc. Solid understanding of machine learning algorithms, neural networks, and deep learning. Experience with data manipulation libraries (Pandas, NumPy) and data visualization tools (Matplotlib, Seaborn). Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models using Docker, Kubernetes. Familiarity with NLP, Computer Vision, or other AI domains is a plus. Strong problem-solving skills and ability to work independently and collaboratively. Excellent communication skills. Experience with distributed computing and big data tools like Spark or Hadoop. Knowledge of MLOps best practices and tools. Familiarity with REST APIs and microservices architecture. Experience with version control systems like Git. Understanding of software development lifecycle (SDLC) and Agile methodologies. What skills and experience are we looking for? Design, develop, and deploy machine learning models and AI algorithms using Python and relevant libraries. Collaborate with cross-functional teams to gather requirements and translate business problems into AI/ML solutions. Optimize and scale machine learning pipelines and systems for production. Perform data preprocessing, feature engineering, and exploratory data analysis. Implement and fine-tune deep learning models using frameworks like TensorFlow, PyTorch, or similar. Conduct experiments and evaluate model performance using statistical methods. Write clean, maintainable, and well-documented code. Mentor junior developers and participate in code reviews. Stay up-to-date with the latest AI/ML research and technologies. Ensure model deployment is seamless and models are integrated with existing infrastructure. Apply (Gmail) Apply (Form)

Join MSBC as an AI/ML Engineer – Deliver Real-World Intelligent Systems At MSBC, we design and implement practical AI solutions that solve real business problems across industries. As an AI/ML Engineer, you will play a key role in building and deploying machine learning models and data-driven systems that are used in production. This role is ideal for engineers with solid hands-on experience delivering end-to-end AI/ML projects. Key Tools and Frameworks • Programming Languages – Python (FastAPI, Flask, Django) • Machine Learning Libraries – scikit-learn, XGBoost, TensorFlow or PyTorch • Data Pipelines – Pandas, Spark, Airflow • Model Deployment – FastAPI, Flask, Docker, MLflow • Cloud Platforms – AWS, GCP, Azure (any one) • Version Control – Git Key Responsibilities • Design and develop machine learning models to address business requirements. • Build and manage data pipelines for training and inference workflows. • Train, evaluate, and optimise models for accuracy and performance. • Deploy models in production environments using containerised solutions. • Work with structured and unstructured data from various sources. • Ensure robust monitoring, retraining, and versioning of models. • Contribute to architecture and design discussions for AI/ML systems. • Document processes, results, and deployment procedures clearly. • Collaborate with software engineers, data engineers, and business teams. Required Skills and Qualifications • 4+ years of hands-on experience delivering ML solutions in production environments. • Strong programming skills in Python and deep understanding of ML fundamentals. • Experience with supervised and unsupervised learning, regression, classification, and clustering techniques. • Practical experience in model deployment and lifecycle management. • Good understanding of data preprocessing, feature engineering, and model evaluation. • Experience with APIs, containers, and cloud deployment. • Familiarity with CI/CD practices and version control. • Ability to work independently and deliver results in fast-paced projects. • Excellent English communication skills for working with distributed teams. • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. MSBC Group has been a trusted technology partner for over 20 years, delivering the latest systems and software solutions for financial services, manufacturing, logistics, construction, and startup ecosystems. Our expertise includes Accessible AI, Custom Software Solutions, Staff Augmentation, Managed Services, and Business Process Outsourcing. We are at the forefront of developing advanced AI-enabled services and supporting transformative projects. Operating globally, we drive innovation, making us a trusted AI and automation partner.