657 Xgboost Jobs - Page 17

Summary Position Summary DT-US Product Engineering - Data Scientist Manager We are seeking an exceptional Data Scientist who combines deep expertise in AI/ML with a strong focus on data quality and advanced analytics. This role requires a proven track record in developing production-grade machine learning solutions, implementing robust data quality frameworks, and leveraging cutting-edge analytical tools to drive business transformation through data-driven insights . Work you will do The Data Scientist will be responsible for developing and implementing end-to-end AI/ML solutions while ensuring data quality excellence across all stages of the data lifecycle. This role requires extensive experience in modern data science platforms, AI frameworks, and analytical tools, with a focus on scalable and production-ready implementations. Project Leadership and Management: Lead complex data science initiatives utilizing Databricks, Dataiku, and modern AI/ML frameworks for end-to-end solution development Establish and maintain data quality frameworks and metrics across all stages of model development Design and implement data validation pipelines and quality control mechanisms for both structured and unstructured data Strategic Development: Develop and deploy advanced machine learning models, including deep learning and generative AI solutions Design and implement automated data quality monitoring systems and anomaly detection frameworks Create and maintain MLOps pipelines for model deployment, monitoring, and maintenance Team Mentoring and Development: Lead and mentor a team of data scientists and analysts, fostering a culture of technical excellence and continuous learning Develop and implement training programs to enhance team capabilities in emerging technologies and methodologies Establish performance metrics and career development pathways for team members Drive knowledge sharing initiatives and best practices across the organization Provide technical guidance and code reviews to ensure high-quality deliverables Data Quality and Governance: Establish data quality standards and best practices for data collection, preprocessing, and feature engineering Implement data validation frameworks and quality checks throughout the ML pipeline Design and maintain data documentation systems and metadata management processes Lead initiatives for data quality improvement and standardization across projects Technical Implementation: Design, develop and deploy end-to-end AI/ML solutions using modern frameworks including TensorFlow, PyTorch, scikit-learn, XGBoost for machine learning, BERT and GPT for NLP, and OpenCV for computer vision applications Architect and implement robust data processing pipelines leveraging enterprise platforms like Databricks, Apache Spark, Pandas for data transformation, Dataiku and Apache Airflow for ETL/ELT processes, and DVC for data version control Establish and maintain production-grade MLOps practices including model deployment, monitoring, A/B testing, and continuous integration/deployment pipelines Technical Expertise Requirements: Must Have: Enterprise AI/ML Platforms: Demonstrate mastery of Databricks for large-scale processing, with proven ability to architect solutions at scale Programming & Analysis: Advanced Python (NumPy, Pandas, scikit-learn), SQL, PySpark with production-level expertise Machine Learning: Deep expertise in TensorFlow or PyTorch, and scikit-learn with proven implementation experience Big Data Technologies: Advanced knowledge of Apache Spark, Databricks, and distributed computing architectures Cloud Platforms: Strong experience with at least one major cloud platform (AWS/Azure/GCP) and their ML services (SageMaker/Azure ML/Vertex AI) Data Processing & Analytics: Extensive experience with enterprise-grade data processing tools and ETL pipelines MLOps & Infrastructure: Proven experience in model deployment, monitoring, and maintaining production ML systems Data Quality: Experience implementing comprehensive data quality frameworks and validation systems Version Control & Collaboration: Strong proficiency with Git, JIRA, and collaborative development practices Database Systems: Expert-level knowledge of both SQL and NoSQL databases for large-scale data management Visualization Tools: Tableau, Power BI, Plotly, Seaborn Large Language Models: Experience with GPT, BERT, LLaMA, and fine-tuning methodologies Good to Have: Additional Programming: R, Julia Additional Big Data: Hadoop, Hive, Apache Kafka Multi-Cloud: Experience across AWS, Azure, and GCP platforms Advanced Analytics: Dataiku, H2O.ai Additional MLOps: MLflow, Kubeflow, DVC (Data Version Control) Data Quality & Validation: Great Expectations, Deequ, Apache Griffin Business Intelligence: SAP HANA, SAP Business Objects, SAP BW Specialized Databases: Cassandra, MongoDB, Neo4j Container Orchestration: Kubernetes, Docker Additional Collaboration Tools: Confluence, BitBucket Education: Advanced degree in quantitative discipline (Statistics, Math, Computer Science, Engineering) or relevant experience. Qualifications: 10-13 years of experience with data mining, statistical modeling tools and underlying algorithms. 5+ years of experience with data analysis software for large scale analysis of structured and unstructured data. Proven track record of leading and delivering large-scale machine learning projects, including production model deployment, data quality framework implementation and experience with very large datasets to create data-driven insights thru predictive and prescriptive analytic models. E xtensive knowledge of supervised and unsupervised analytic modeling techniques such as linear and logistic regression, support vector machines, decision trees / random forests, Naïve-Bayesian, neural networks, association rules, text mining, and k-nearest neighbors among other clustering models. Extensive experience with deep learning frameworks, automated ML platforms, data processing tools (Databricks Delta Lake, Apache Spark), analytics platforms (Tableau, Power BI), and major cloud providers (AWS, Azure, GCP) Experience architecting and implementing enterprise-grade solutions using cloud-native ML services while ensuring cost optimization and performance efficiency Strong track record of team leadership, stakeholder management, and driving technical excellence across multiple concurrent projects Expert-level proficiency in Python, R, and SQL, with deep understanding of statistical analysis, hypothesis testing, feature engineering, model evaluation, and validation techniques in production environments Demonstrated leadership experience in implementing MLOps practices, including model monitoring, A/B testing frameworks, and maintaining production ML systems at scale. Working knowledge of supervised and unsupervised learning techniques, such as Regression/Generalized Linear Models, decision tree analysis, boosting and bagging, Principal Components Analysis, and clustering methods. Strong oral and written communication skills, including presentation skills The Team Information Technology Services (ITS) helps power Deloitte’s success. ITS drives Deloitte, which serves many of the world’s largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence. The ~3,000 professionals in ITS deliver services including: Security, risk & compliance Technology support Infrastructure Applications Relationship management Strategy Deployment PMO Financials Communications Product Engineering (PxE) Product Engineering (PxE) team is the internal software and applications development team responsible for delivering leading-edge technologies to Deloitte professionals. Their broad portfolio includes web and mobile productivity tools that empower our people to log expenses, enter timesheets, book travel and more, anywhere, anytime. PxE enables our client service professionals through a comprehensive suite of applications across the business lines. In addition to application delivery, PxE offers full-scale design services, a robust mobile portfolio, cutting-edge analytics, and innovative custom development. Work Location: Hyderabad Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Professional development At Deloitte, professionals have the opportunity to work with some of the best and discover what works best for them. Here, we prioritize professional growth, offering diverse learning and networking opportunities to help accelerate careers and enhance leadership skills. Our state-of-the-art DU: The Leadership Center in India, located in Hyderabad, represents a tangible symbol of our commitment to the holistic growth and development of our people. Explore DU: The Leadership Center in India . Benefits To Help You Thrive At Deloitte, we know that great people make a great organization. Our comprehensive rewards program helps us deliver a distinctly Deloitte experience that helps that empowers our professionals to thrive mentally, physically, and financially—and live their purpose. To support our professionals and their loved ones, we offer a broad range of benefits. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Requisition code: 303069 Show more Show less

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 3-6 years of relevant experience in Machine Learning, AI, or Data Science roles. OR M.Tech, M. Statistics with 2-4 years of relevant experience in 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 2 college or similar colleges/universities. Technical Skills: Proficiency in programming languages such as Python & R Strong knowledge of classical machine 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 with ML frameworks like TensorFlow, PyTorch, Scikit-learn, or Keras. Building & deploying Model APIs using framework like Flask, Fast API, Django, TensorFlow Serving etc. Knowledge of cloud platforms like Azure (preferred), AWS, GCP and experience deploying models in such environments -> changed the wording, added points. Nice to Have: Object Oriented Programming. Familiarity with NLP, or time series analysis. -> Moving this into Nice to have, not bare min Exposure to deep learning models (RNN, LSTM) and working with GPUs. Show more Show less

About Aviso AI: Aviso AI is revolutionizing enterprise sales intelligence with its cutting-edge AI solutions for forecasting, deal guidance, and revenue operations. By leveraging AI and machine learning, we transform how enterprise teams operate, allowing them to make data-driven decisions, optimize sales strategies, and increase productivity. We are seeking an experienced and hands-on Manager / Senior Manager – Data Science to lead a team of data scientists while actively contributing to technical development. This hybrid role combines individual contribution with team leadership, ideal for someone who thrives on mentoring others while solving complex modeling challenges. You will report directly to the VP – Data Science and play a key role in shaping Aviso’s AI strategy and execution. Job Title: Manager / Senior Manager – Data Science Key Responsibilities: Lead a team of data scientists, setting direction, providing technical mentorship, and driving delivery across multiple projects. Remain individually hands-on in problem-solving, experimentation, and model development. Translate business and product needs into clear data science problems and actionable solutions. Collaborate cross-functionally with product, engineering, and GTM teams to deliver intelligent platform capabilities. Uphold best practices in model validation, reproducibility, and productionization. Communicate results and model impact to stakeholders, including senior leadership. Align team efforts with company-level ML/AI strategy in collaboration with the VP – Data Science. Qualifications: 7+ years of experience in data science, with at least 2 years in a leadership or pod-lead role. Expertise in Python, ML libraries (scikit-learn, XGBoost, TensorFlow, etc.), and SQL. Strong grasp of machine learning theory, experimentation design, and production deployment. Experience with cloud data ecosystems (AWS, GCP, or Databricks). Proven ability to deliver business impact through data-driven solutions. Excellent communication and collaboration skills. Prior exposure to SaaS, RevOps, or GTM intelligence platforms is a strong plus. Why Join Aviso AI? At Aviso AI, you’ll work in a collaborative environment alongside talented engineers, product managers, and data scientists. We’re committed to pushing the boundaries of AI and delivering industry-leading solutions that transform how enterprise sales teams operate. You’ll have the opportunity to work on exciting projects that apply advanced AI to real-world business problems and see the direct impact of your work. Location: Remote Reporting To: Vice President – Data Science Employment Type: Full-time Role Type: Individual Contributor + Team Lead (IC + Manager) Show more Show less

Relocation Assistance Offered Within Country Job Number #167664 - Mumbai, Maharashtra, India Who We Are Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name! Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all. Title: Assistant Manager, Global Data Science Brief introduction - Role Summary/Purpose: The Global Data Science team at Colgate-Palmolive builds and deploys analytics solutions to drive business growth, focusing on areas like Price Elasticity, Trade Promo Efficiency, and Marketing Effectiveness. To meet increasing demand, new geographically based "Advanced Analytics Pods" are being created, with this role leading the "Europe and Africa Eurasia Pod" and managing six data scientists. This position involves close collaboration with the capability center, Division Analytics and business teams to understand needs, prioritize projects, and deliver relevant analytics solutions. The role requires strong expertise in statistical data analytics, machine learning/AI, and CPG analytics to develop predictive models, manage large datasets, and translate insights into business impact. Responsibilities: Leads the scoping and delivery of Pricing, Promotion, and Marketing Effectiveness analytics, including conceptualizing and building predictive models, machine learning algorithms, and optimization solutions. Plays a key role in the governance and continuous improvement of internal analytics solutions, collaborating with other Advanced Analytics Pods. Translates complex analytical results and insights into easily understandable and actionable recommendations for business teams, effectively bridging the gap between business needs and data science. Develops and manages visualization deliverables and web applications to enable self-service analytics and diagnostics for various functions. Writes SQL and Python code to build and deploy scalable enterprise-level data science solutions (e.g., Marketing Mix Modeling, Revenue Growth Management) on cloud platforms using tools like Airflow, Docker, and Kubernetes. Leads, mentors, and coaches a team of data scientists, ensuring the quality of recommendations and solutions deployed globally, and drives new value by integrating internal and external data. Collaborates effectively with cross-functional teams (GIT, Data Architecture, Analytics Engineering) and business partners across geographies and time zones, assisting with change management and presenting insights to stakeholders. Required Qualifications: Educational Background & Experience: Requires a Bachelor's degree (Master's/MBA preferred) in a quantitative/technical field (Data Science, Engineering, Statistics, Economics, etc.) with 7+ years in data science and analytics, including 2+ years managing/setting up a data science team. Advanced Technical Expertise: Strong hands-on experience developing and deploying statistical models and machine learning algorithms (Regression, Random Forest, XGBOOST, Clustering, etc.) in production, with expert coding skills in Python, SQL, PySpark, and R. MLOps & Cloud Proficiency: Demonstrable experience with MLOps practices (GitHub, Airflow, Docker, Kubernetes, Databricks, Dataiku) and cloud platforms like Google Cloud and Snowflake, managing high-volume, varied data sources. Domain Specialization & Business Acumen: Expert knowledge in Marketing Mix Modeling, Revenue Growth Management, Optimization, Forecasting, and Marketing Analytics, preferably in CPG or consulting, with the ability to think strategically in complex business contexts. Client-Facing & Communication Skills: Proven experience in a client-facing role, supporting multi-functional teams, with exceptional communication, collaboration, presentation, and storytelling skills to convey insights to business stakeholders. Project Leadership & Execution: Ability to independently plan and execute deliveries, lead project teams for predictive modeling and ad-hoc data needs, and build processes for data transformation and management. Preferred Qualifications: Proficient in building web applications using frameworks like Pydash, Plotly, R Shiny, Streamlit, Django, Dash, Python Flask, React.js, or Angular JS. Experienced with advanced AI and machine learning concepts including Deep Learning, Reinforcement Learning, Image Recognition, GenAI, and understanding the real-world application of various ML techniques. Strong knowledge of cloud environments and MLOps tools, including Databricks, Docker, Azure Data Factory, machine learning APIs (Azure, AWS, Vertex AI), Snowflake, and Google Cloud components (Cloud Build, Cloud Run, Kubernetes). Familiar with data visualization tools (Domo, Looker, Streamlit), working with third-party data (syndicated market data, Point of Sales), and has experience in Data Science roles within the CPG industry, ideally in relevant geographies. Our Commitment to Inclusion Our journey begins with our people—developing strong talent with diverse backgrounds and perspectives to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business. Equal Opportunity Employer Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law. Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation. #LI-Remote

Requisition ID 167664 - Posted 06/19/2025 - Analytics - India - Maharashtra - Mumbai - Colgate-Palmolive - No Travel - Remote Relocation Assistance Offered Within Country Job Number #167664 - Mumbai, Maharashtra, India Who We Are Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name! Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all. Title: Assistant Manager, Global Data Science Brief introduction - Role Summary/Purpose: The Global Data Science team at Colgate-Palmolive builds and deploys analytics solutions to drive business growth, focusing on areas like Price Elasticity, Trade Promo Efficiency, and Marketing Effectiveness. To meet increasing demand, new geographically based "Advanced Analytics Pods" are being created, with this role leading the "Europe and Africa Eurasia Pod" and managing six data scientists. This position involves close collaboration with the capability center, Division Analytics and business teams to understand needs, prioritize projects, and deliver relevant analytics solutions. The role requires strong expertise in statistical data analytics, machine learning/AI, and CPG analytics to develop predictive models, manage large datasets, and translate insights into business impact. Responsibilities: Leads the scoping and delivery of Pricing, Promotion, and Marketing Effectiveness analytics, including conceptualizing and building predictive models, machine learning algorithms, and optimization solutions. Plays a key role in the governance and continuous improvement of internal analytics solutions, collaborating with other Advanced Analytics Pods. Translates complex analytical results and insights into easily understandable and actionable recommendations for business teams, effectively bridging the gap between business needs and data science. Develops and manages visualization deliverables and web applications to enable self-service analytics and diagnostics for various functions. Writes SQL and Python code to build and deploy scalable enterprise-level data science solutions (e.g., Marketing Mix Modeling, Revenue Growth Management) on cloud platforms using tools like Airflow, Docker, and Kubernetes. Leads, mentors, and coaches a team of data scientists, ensuring the quality of recommendations and solutions deployed globally, and drives new value by integrating internal and external data. Collaborates effectively with cross-functional teams (GIT, Data Architecture, Analytics Engineering) and business partners across geographies and time zones, assisting with change management and presenting insights to stakeholders. Required Qualifications: Educational Background & Experience: Requires a Bachelor's degree (Master's/MBA preferred) in a quantitative/technical field (Data Science, Engineering, Statistics, Economics, etc.) with 7+ years in data science and analytics, including 2+ years managing/setting up a data science team. Advanced Technical Expertise: Strong hands-on experience developing and deploying statistical models and machine learning algorithms (Regression, Random Forest, XGBOOST, Clustering, etc.) in production, with expert coding skills in Python, SQL, PySpark, and R. MLOps & Cloud Proficiency: Demonstrable experience with MLOps practices (GitHub, Airflow, Docker, Kubernetes, Databricks, Dataiku) and cloud platforms like Google Cloud and Snowflake, managing high-volume, varied data sources. Domain Specialization & Business Acumen: Expert knowledge in Marketing Mix Modeling, Revenue Growth Management, Optimization, Forecasting, and Marketing Analytics, preferably in CPG or consulting, with the ability to think strategically in complex business contexts. Client-Facing & Communication Skills: Proven experience in a client-facing role, supporting multi-functional teams, with exceptional communication, collaboration, presentation, and storytelling skills to convey insights to business stakeholders. Project Leadership & Execution: Ability to independently plan and execute deliveries, lead project teams for predictive modeling and ad-hoc data needs, and build processes for data transformation and management. Preferred Qualifications: Proficient in building web applications using frameworks like Pydash, Plotly, R Shiny, Streamlit, Django, Dash, Python Flask, React.js, or Angular JS. Experienced with advanced AI and machine learning concepts including Deep Learning, Reinforcement Learning, Image Recognition, GenAI, and understanding the real-world application of various ML techniques. Strong knowledge of cloud environments and MLOps tools, including Databricks, Docker, Azure Data Factory, machine learning APIs (Azure, AWS, Vertex AI), Snowflake, and Google Cloud components (Cloud Build, Cloud Run, Kubernetes). Familiar with data visualization tools (Domo, Looker, Streamlit), working with third-party data (syndicated market data, Point of Sales), and has experience in Data Science roles within the CPG industry, ideally in relevant geographies. Our Commitment to Inclusion Our journey begins with our people—developing strong talent with diverse backgrounds and perspectives to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business. Equal Opportunity Employer Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law. Reasonable accommodation during the application process is available for persons with disabilities. Please complete this request form should you require accommodation. #LI-Remote

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: What you need to know about the role- Data scientists are highly motivated team players with strong analytical skills who specialize in creating, driving and executing initiatives to mitigate fraud on PayPal’s platform and improve the experience for PayPal’s hundreds of millions of customers, while guaranteeing compliance with regulations. Meet our team Data scientists in the Fraud Risk team are problem solvers suited to approach varied challenges in complex big data environments. Our core goals are to enable seamless and delightful experiences to our customers, while preventing threat actors from accessing customers’ financial instruments and personal information. As part of our day-to-day job, we are collaborating with a wide variety of partners: product owners, data scientists, security experts, legal consults, and engineers, to bring our data science insights to life, impacting the experience and security of millions of customers around the globe. Job Description: Your way to impact Data scientists deeply understand PayPal’s business objectives, as their impact on PayPal’s top and bottom lines is immense. As a data scientist, you will develop key AIML capabilities, tools, and insights with the aim of adapting PayPal’s advanced proprietary fraud prevention and experience mechanisms and enabling growth. Your day to day Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets. What Do You Need To Bring- Strong proficiency in Python for data analysis, machine learning, and automation. Solid understanding of supervised and unsupervised AI/machine learning methods (e.g., XGBoost, LightGBM, Random Forest, clustering, isolation forests, autoencoders, neural networks, transformer-based architectures). Experience in payment fraud, AML, KYC, or broader risk modeling within fintech or financial institutions. Experience developing and deploying ML models in production using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. Hands-on experience with LLMs (e.g., OpenAI, LLaMA, Claude, Mistral), including use of prompt engineering, retrieval-augmented generation (RAG), and agentic AI to support internal automation and risk workflows. Ability to work cross-functionally with engineering, product, compliance, and operations teams. Proven track record of translating complex ML insights into business actions or policy decisions. BS/BA degree with 3+ years of related professional experience or master’s degree with 1+ years of related experience. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. REQ ID R0127047 Show more Show less

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Description Summary: What you need to know about the role- Data scientists are highly motivated team players with strong analytical skills who specialize in creating, driving and executing initiatives to mitigate fraud on PayPal’s platform and improve the experience for PayPal’s hundreds of millions of customers, while guaranteeing compliance with regulations. Meet our team Data scientists in the Fraud Risk team are problem solvers suited to approach varied challenges in complex big data environments. Our core goals are to enable seamless and delightful experiences to our customers, while preventing threat actors from accessing customers’ financial instruments and personal information. As part of our day-to-day job, we are collaborating with a wide variety of partners: product owners, data scientists, security experts, legal consults, and engineers, to bring our data science insights to life, impacting the experience and security of millions of customers around the globe. Job Description: Your way to impact Data scientists deeply understand PayPal’s business objectives, as their impact on PayPal’s top and bottom lines is immense. As a data scientist, you will develop key AIML capabilities, tools, and insights with the aim of adapting PayPal’s advanced proprietary fraud prevention and experience mechanisms and enabling growth. Your day to day Day-to-day duties include data analysis, monitoring and forecasting, creating the logic for and implementing risk rules and strategies, providing requirements to data scientists and technology teams on attribute, model and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets. What Do You Need To Bring- Strong proficiency in Python for data analysis, machine learning, and automation. Solid understanding of supervised and unsupervised AI/machine learning methods (e.g., XGBoost, LightGBM, Random Forest, clustering, isolation forests, autoencoders, neural networks, transformer-based architectures). Experience in payment fraud, AML, KYC, or broader risk modeling within fintech or financial institutions. Experience developing and deploying ML models in production using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. Hands-on experience with LLMs (e.g., OpenAI, LLaMA, Claude, Mistral), including use of prompt engineering, retrieval-augmented generation (RAG), and agentic AI to support internal automation and risk workflows. Ability to work cross-functionally with engineering, product, compliance, and operations teams. Proven track record of translating complex ML insights into business actions or policy decisions. BS/BA degree with 3+ years of related professional experience or master’s degree with 1+ years of related experience. For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply. REQ ID R0127047 Show more Show less

We're Hiring: Data Scientist Databricks & ML Deployment Expert Location: Mumbai/Pune Experience: 38 Years Apply Now! Are you passionate about deploying real-world machine learning solutions? We're looking for a versatile Data Scientist with deep expertise in Databricks, PySpark , and end-to-end ML deployment to drive impactful projects in the Retail and Automotive domains. What Youll Do Develop scalable ML models (Regression, Classification, Clustering) Deliver advanced use cases like CLV modeling , Predictive Maintenance , and Time Series Forecasting Design and automate ML workflows on Databricks using PySpark Build and deploy APIs to serve ML models (Flask, FastAPI, Django) Own model deployment and monitoring in production environments Work closely with Data Engineering and DevOps teams for CI/CD integration Optimize pipelines and model performance (code & infrastructure level) Must-Have Skills Strong hands-on with Databricks and PySpark Proven track record in ML model development & deployment (min. 2 production deployments) Solid grasp of Regression, Classification, Clustering & Time Series Proficiency in SQL , workflow automation, and ELT/ETL processes API development (Flask, FastAPI, Django) CI/CD, deployment automation, and ML pipeline optimization Familiarity with Medallion Architecture Domain Expertise Retail : CLV, Pricing, Demand Forecasting Automotive : Predictive Maintenance, Time Series Nice to Have MLflow, Docker, Kubernetes Cloud: Azure, AWS, or GCP If you're excited to build production-ready ML systems that create real business impact, we want to hear from you! Apply Now to chaity.mukherjee@celebaltech.com.

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

Job Description: (Mandate Skills) What We Are Looking For Data Scientist preferably from financial services, large banks/MNCs. Strong background in business analysis (consumer/business strategy, financial products, pricing, etc.) with very strong data analysis (Sql, excel, etc,) experience Strong understanding of how to structure analysis and to solve real world business problems. Ability to identify key drivers of business and create KPIs/modeling solutions for the same, Expertise in end-to-end model development and model lifecycle management (develop, deploy, monitor) is Preferred Exposure/Experience in developing Machine Learning models using various algorithms (logistic/linear, Random Forest. Xgboost ,etc) Hands on experience in R or Python is must Exposure to unstructured data analytics and big data handling is a plus Good business understanding of fintech/personal lending space is preferred Responsibilities You'll work closely with the Product and Risk Team to: Define, design and deliver solutions using data science/analytics in fast paced environment Evaluate and apply machine learning algorithms to build variety of data science models particularly in credit risk/unsecured lending domain but not limited to Complete ownership including but not limited to identifying model development approaches, building ML models, evaluation, cost benefit analysis, exploration of new data sources, implementation and monitoring of developed models. Working closely with the engineering team for deployment of models and infrastructure development. Skills: unstructured data analytics,business analysis,big data,python,machine learning,data science,sql,analytics,model development,excel,models,r Show more Show less

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems. The Opportunity When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills. As part of the Data Science team you will design and deliver scalable AI applications that drive business transformation. As a Senior Associate you will analyze complex problems, mentor junior team members, and build meaningful client connections while navigating the evolving landscape of AI and machine learning. This role offers the chance to work on innovative technologies, collaborate with cross-functional teams, and contribute to creative solutions that shape the future of the industry. Responsibilities Design and implement scalable AI applications to facilitate business transformation Analyze intricate problems and propose practical solutions Mentor junior team members to enhance their skills and knowledge Establish and nurture meaningful relationships with clients Navigate the dynamic landscape of AI and machine learning Collaborate with cross-functional teams to drive innovative solutions Utilize advanced technologies to improve project outcomes Contribute to the overall strategy of the Data Science team What You Must Have Bachelor's Degree in Computer Science, Engineering, or equivalent technical discipline 4-9 years of experience in Data Science/ML/AI roles Oral and written proficiency in English required What Sets You Apart Proficiency in Python and data science libraries Hands-on experience with Generative AI and prompt engineering Familiarity with cloud platforms like Azure, AWS, GCP Understanding of production-level AI systems and CI/CD Experience with Docker, Kubernetes for ML workloads Knowledge of MLOps tooling and pipelines Demonstrated track record of delivering AI-driven solutions Preferred Knowledge/Skills Please reference About PwC CTIO – AI Engineering PwC’s Commercial Technology and Innovation Office (CTIO) is at the forefront of emerging technology, focused on building transformative AI-powered products and driving enterprise innovation. The AI Engineering team within CTIO is dedicated to researching, developing, and operationalizing cutting-edge technologies such as Generative AI, Large Language Models (LLMs), AI Agents, and more. Our mission is to continuously explore what's next—enabling business transformation through scalable AI/ML solutions while remaining grounded in research, experimentation, and engineering excellence.ill categories for job description details. Role Overview We are seeking a Senior Associate – Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 4 to 9 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI, including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems. Show more Show less

Greetings from HCLTECH We are hiring for Data Scientist candidates @Bangalore Role: Data Scientist Location: Bangalore Experience: 7+ years (Mandatory) Work Mode: Hybrid (Compulsory) Mandatory Skills: #machinelearning #aws #mlops #python #artificialintelligence Job Description: Data Science, Machine Learning, Advanced Analytics Basic understanding of how models are deployed, scaled, consumed and monitored. Kubeflow preferred Experience in Azure services, security, integration and AI services Data Analysis and Modelling Spark / Tensorflow/ Pytorch/ Scikit-learn/ xgboost Advanced statistical data analysis, machine learning techniques, Bayesian methods, MCMC, neural networks, ensemble methods, Gaussian processes, graph analytics RDBMS, NoSQL Handson with Python Natural Language Processing and libraries like NLTK etc. Communication & Presentation Skill Ability to Analyze, comprehend and respond to situation Interpersonal skill, adaptability, flexibility Interested candidates, please share the resume to amrin.a@hcltech.com Show more Show less

Data Scientist - Retail & E-commerce Analytics with Personalization, Campaigns & GCP/BigQuery Expertise We are looking for a skilled Data Scientist with strong expertise in Retail & E-commerce Analytics , particularly in personalization , campaign optimization , and Generative AI (GenAI) , along with hands-on experience working with Google Cloud Platform (GCP) and BigQuery . The ideal candidate will use data science methodologies and advanced machine learning techniques to drive personalized customer experiences, optimize marketing campaigns, and create innovative solutions for the retail and e-commerce business. This role will also involve working with large-scale datasets on GCP and performing high-performance analytics using BigQuery . Responsibilities E-commerce Analytics & Personalization : Develop and implement machine learning models for personalized recommendations , product search optimization , and customer segmentation to improve the online shopping experience. Analyze customer behavior data to create tailored experiences that drive engagement, conversions, and customer lifetime value. Build recommendation systems using collaborative filtering , content-based filtering , and hybrid approaches. Use predictive modeling techniques to forecast customer behavior, sales trends, and optimize inventory management. Campaign Optimization Analyze and optimize digital marketing campaigns across various channels (email, social media, display ads, etc.) using statistical analysis and A/B testing methodologies. Build predictive models to measure campaign performance, improving targeting, content, and budget allocation. Utilize customer data to create hyper-targeted campaigns that increase customer acquisition, retention, and conversion rates. Evaluate customer interactions and campaign performance to provide insights and strategies for future optimization. Generative AI (GenAI) & Innovation Use Generative AI (GenAI) techniques to dynamically generate personalized content for marketing, such as product descriptions, email content, and banner designs. Leverage Generative AI to synthesize synthetic data, enhance existing datasets, and improve model performance. Work with teams to incorporate GenAI solutions into automated customer service chatbots, personalized product recommendations, and digital content creation. Big Data Analytics With GCP & BigQuery Leverage Google Cloud Platform (GCP) for scalable data processing, machine learning, and advanced analytics. Utilize BigQuery for large-scale data querying, processing, and building data pipelines, allowing efficient data handling and analytics at scale. Optimize data workflows on GCP using tools like Cloud Storage , Cloud Functions , Cloud Dataproc , and Dataflow to ensure data is clean, reliable, and accessible for analysis. Collaborate with engineering teams to maintain and optimize data infrastructure for real-time and batch data processing in GCP. Data Analysis & Insights Perform data analysis across customer behavior, sales, and marketing datasets to uncover insights that drive business decisions. Develop interactive reports and dashboards using Google Data Studio to visualize key performance metrics and findings. Provide actionable insights on key e-commerce KPIs such as conversion rate , average order value (AOV) , customer lifetime value (CLV) , and cart abandonment rate . Collaboration & Cross-Functional Engagement Work closely with marketing, product, and technical teams to ensure that data-driven insights are used to inform business strategies and optimize retail e-commerce operations. Communicate findings and technical concepts effectively to stakeholders, ensuring they are actionable and aligned with business goals. Key Technical Skills Machine Learning & Data Science : Proficiency in Python or R for data manipulation, machine learning model development (scikit-learn, XGBoost, LightGBM), and statistical analysis. Experience building recommendation systems and personalization algorithms (e.g., collaborative filtering, content-based filtering). Familiarity with Generative AI (GenAI) technologies, including transformer models (e.g., GPT), GANs , and BERT for content generation and data augmentation. Knowledge of A/B testing and multivariate testing for campaign analysis and optimization. Big Data & Cloud Analytics Hands-on experience with Google Cloud Platform (GCP) , specifically BigQuery for large-scale data analytics and querying. Familiarity with BigQuery ML for running machine learning models directly in BigQuery. Experience working with GCP tools like Cloud Dataproc , Cloud Functions , Cloud Storage , and Dataflow to build scalable and efficient data pipelines. Expertise in SQL for data querying, analysis, and optimization of data workflows in BigQuery . E-commerce & Retail Analytics Strong understanding of e-commerce metrics such as conversion rates , AOV , CLV , and cart abandonment . Experience with analytics tools like Google Analytics , Adobe Analytics , or similar platforms for web and marketing data analysis. Data Visualization & Reporting Proficiency in data visualization tools like Tableau , Power BI , or Google Data Studio to create clear, actionable insights for business teams. Experience developing dashboards and reports that monitor KPIs and e-commerce performance. Desired Qualifications Bachelor's or Master's degree in Computer Science , Data Science , Statistics , Engineering , or related fields. 5+ years of experience in data science , machine learning , and e-commerce analytics , with a strong focus on personalization , campaign optimization , and Generative AI . Hands-on experience working with GCP and BigQuery for data analytics, processing, and machine learning at scale. Proven experience in a client-facing role or collaborating cross-functionally with product, marketing, and technical teams to deliver data-driven solutions. Strong problem-solving abilities, with the ability to analyze large datasets and turn them into actionable insights for business growth. Show more Show less

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. Salary - 30K CTC TO 35K CTC 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. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Show more Show less

Job Description Build robust ML pipelines and automate model training, evaluation, and deployment. Optimize and tune models for financial time-series, pricing engines, and fraud detection. Collaborate with data scientists and data engineers to deploy scalable and secure ML models. Monitor model drift, data drift, and ensure models are retrained and updated as per regulatory norms. Implement CI/CD for ML and integrate with enterprise applications. Tech Stack Languages: Python ML Platforms: MLflow, Kubeflow MLOps Tools: Airflow, MLReef, Seldon Libraries: scikit-learn, XGBoost, LightGBM Cloud: GCP AI Platform Containerization: Docker, Kubernetes Job Category: AI/ML Engineer Job Type: Full Time Job Location: Mumbai Exp-Level: 3 to 5 Years Apply for this position Full Name * Email * Phone * Cover Letter * Upload CV/Resume *Allowed Type(s): .pdf, .doc, .docx By using this form you agree with the storage and handling of your data by this website. * Recent Comments Show more Show less

@SynapseIndia We're Hiring #Designation- Sr Software Engineer(PYTHON ) #Eperience: 4+ years #Location: NSEZ, Sector 81, Noida #OnlyImmediateJoiner #WorkFromOffice Interested Candidate , share resume on surbhib@synapseco.com JOB DESCRIPTION We are looking for a highly skilled Senior Python AI/ML Developer to join our team. The ideal candidate will have extensive experience designing, developing, and deploying machine learning models and AI solutions using Python. You will collaborate with data scientists, engineers, and product teams to build scalable, efficient, and innovative AI-driven applications. Roles & Responsibilities 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 pre-processing, 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. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field. 5+ 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. Interested Candidate , share resume on surbhib@synapseco.com #PythonDevelopment #PythonAIML #PythonDeveloper #AI/ML #CloudPlatform #Pythontools #ImmediateJoiner Show more Show less

Job Title: Senior Data Scientist (Advanced Modeling & Machine Learning) Location: Remote Job Type: Full-time About the role We are seeking a highly motivated and experienced Senior Data Scientist with a strong background in statistical modeling, machine learning, and natural language processing (NLP). This individual will work on advanced attribution models and predictive algorithms that power strategic decision-making across the business. The ideal candidate will have a Master’s degree in a quantitative field, 4–6 years of hands-on experience, and demonstrated expertise in building models from linear regression to cutting-edge deep learning and large language models (LLMs). A Ph.D. is strongly preferred. Responsibilities Responsible for analyzing the data, identifying patterns, and do a detailed EDA. Build and refine predictive models using techniques such as linear/logistic regression, XGBoost, and neural networks. Leverage machine learning and NLP methods to analyze large-scale structured and unstructured datasets. Apply LLMs and transformers to develop solutions in content understanding, summarization, classification, and retrieval. Collaborate with data engineers and product teams to deploy scalable data pipelines and model production systems. Interpret model results, generate actionable insights, and present findings to technical and non-technical stakeholders. Stay abreast of the latest research and integrate cutting-edge techniques into ongoing projects Required Qualifications Master’s degree in Computer Science, Statistics, Applied Mathematics, or a related field. 4–6 years of industry experience in data science or machine learning roles. Strong statistical foundation, with practical experience in regression modeling, hypothesis testing, and A/B testing. Hands-on knowledge of: > Programming languages : Python (primary), SQL, R (optional) > Libraries : pandas, NumPy, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, spaCy, Hugging Face Transformers > Distributed computing : PySpark, Dask > Big Data and Cloud Platforms : Databricks, AWS Sagemaker, Google Vertex AI, Azure ML > Data Engineering Tools : Apache Spark, Delta Lake, Airflow > ML Workflow & Visualization : MLflow, Weights & Biases, Plotly, Seaborn, Matplotlib > Version control and collaboration : Git, GitHub, Jupyter, VSCode Preferred Qualifications Masters or Ph.D. in a quantitative or technical field. Experience with deploying machine learning pipelines in production using CI/CD tools. Familiarity with containerization (Docker) and orchestration (Kubernetes) in ML workloads. Understanding of MLOps and model lifecycle management best practices. Experience in real-time data processing (Kafka, Flink) and high-throughput ML systems. What We Offer Competitive salary and performance bonuses Flexible working hours and remote options Opportunities for continued learning and research Collaborative, high-impact team environment Access to cutting-edge technology and compute resources To apply, send your resume to jobs@megovation.io to be part of a team pushing the boundaries of data-driven innovation. Show more Show less

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! Our Company Changing the world through digital experiences is what Adobe’s all about! We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences. We’re passionate about empowering people to craft alluring and powerful images, videos, and apps, and transform how companies harmonize with customers across every screen. We’re on a mission to hire the very best and are committed to building exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new insights can come from everywhere in the organization, and we know the next big idea could be yours. The Opportunity Use your expertise in data science engineering to drive the next stage of growth at Adobe. The Customer Analytics & GTM team is focused on using the power of data to deliver optimized experiences through personalization. This role will drive data engineering for large-scale data science initiatives across a wide variety of strategic projects. As a member of the Data Science Engineering team, you will have significant responsibility to help build large scale cloud-based data and analytics platform with enterprise-wide consumers. This role is inherently multi-functional, and the ideal candidate will work across teams. The position requires ability to own things, come up with innovative solutions, try new tools, technologies, and entrepreneurial personality. Come join us for a truly exciting career, best benefits and outstanding work life balance. What You Will Do Build fault tolerant, scalable, quality data pipelines using multiple cloud- based tools. Develop analytical, personalization capabilities using pioneering technologies by bringing to bear Adobe tools. Build LLM agents to optimize and automate data pipelines following the best engineering practices. Deliver End to End Data Pipelines to run Machine Learning Models in a production platform. Innovative solutions to help broader organization take significant actions fast and efficiently. Chip into data engineering and data science frameworks, tools, and processes. Implement outstanding data operations and implement standard methodologies to use resources in an optimum way. Architect data ingestion, data transformation, data consumption, data governance frameworks. Help build production grade ML models and integration with operational systems. This is a high visibility role for a team which is on a critical mission to stop software privacy. A lot of collaboration with global multi-functional operations teams is required to onboard the customers to use genuine software. Work in a collaborative environment and contribute to the team as well as organization’s success. What You Will Need Bachelor’s degree in computer science or equivalent. Master’s degree or equivalent experience is preferred. 5-8 years of consistent track record as a data engineer. At least 2+ years of demonstrable experience and proven track record with Mobile data ecosystem is a must. App Store Optimization (ASO), 3rd Party systems like Branch, Revenue Cat, Google and Apple APIs etc. building data pipelines for In App purchases, Paywall impressions and tracking, App crashes etc. 5+ years validated ability in distributed data technologies e.g., Hadoop, Hive, Presto, Spark etc. 3+ years of experience with Cloud based technologies – Databricks, S3, Azure Blob Storage, Notebooks, AWS EMR, Athena, Glue etc. Familiarity and usage of different file formats in batch/streaming processing i.e., Delta/Parquet/ORC etc. 2+ years’ experience with streaming data ingestion and transformation using Kafka, Kinesis etc. Outstanding SQL experience. Ability to write optimized SQLs across platforms. Proven hands-on experience in Python/PySpark/Scala and ability to manipulate data using Pandas, NumPy, Koalas etc. and using APIs to transfer data. Experience working as an architect to design large scale distributed data platforms. Experience with CI/CD tools i.e., GitHub, Jenkins etc. Working experience with Open- source orchestration tools i.e., Apache Air Flow/ Azkaban etc. Teammate with excellent communication/teamwork skills when it comes to closely working with data scientists and machine learning engineers daily. Hands-on work experience with Elastic Stack (Elastic, Logstash, Kibana) and Graph Databases (neo4j, Neptune etc.) is highly desired. Work experience with ML algorithms & frameworks i.e., Keras, Tensor Flow, PyTorch, XGBoost, Linear Regression, Classification, Random Forest, Clustering, mlFlow etc. Nice to have Showcase your work if you are an open - source contributor. Passion to contribute to Open-source community is highly valued. Experience with Data Governance tools e.g., Collibra and Collaboration tools e.g., JIRA/ Confluence etc. Familiarity with Adobe tools like Adobe Experience Platform, Adobe Analytics, Customer Journey Analytics, Adobe Journey Optimizer is a plus. Experience with LLM Models/ Agentic workflows using Copilot, Claude, LLAMA, Databricks Genie etc. is highly preferred. Opportunity and affirmative action employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015. Adobe values a free and open marketplace for all employees and has policies in place to ensure that we do not enter into illegal agreements with other companies to not recruit or hire each other’s employees. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more about our vision here. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015. Show more Show less

At Medtronic you can begin a life-long career of exploration and innovation, while helping champion healthcare access and equity for all. You’ll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world. A Day in the Life As a Data Scientist, where you will develop and deploy machine learning models, conduct advanced analytics, and translate data-driven insights into business value. You will work closely with Finance, Engineering, and Business teams to drive data science initiatives and enhance decision-making. Data Scientist – Global Finance Analytics COE Careers that Change Lives Join our Global Finance Analytics Center of Excellence (COE) as a Data Scientist , where you will develop and deploy machine learning models, conduct advanced analytics, and translate data-driven insights into business value. You will work closely with Finance, Engineering, and Business teams to drive data science initiatives and enhance decision-making. This role requires an average of 2-3 days per week of overlapping work hours with the USA team to ensure seamless collaboration. A Day in the Life As a Data Scientist , you will: Develop and deploy AI/ML models for forecasting, anomaly detection, and optimization in financial and business analytics. Work with structured and unstructured data, ensuring data quality, feature engineering, and model interpretability. Collaborate with Data Engineers to build scalable data pipelines and integrate machine learning solutions into production systems. Perform exploratory data analysis (EDA) and statistical modeling to uncover insights and trends. Optimize algorithms for performance, scalability, and business relevance. Present complex findings in an understandable and actionable manner to senior stakeholders. Continuously explore new AI/ML methodologies and tools to enhance analytical capabilities. Must Have: Minimum Requirements Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. 5+ years of experience in AI/ML, predictive modeling, and statistical analysis. Strong proficiency in Python, SQL, and cloud platforms (Azure, AWS, or GCP). Experience with machine learning frameworks such as TensorFlow, Scikit-Learn, PyTorch, or XGBoost. Exposure to financial data modeling and analytics. Strong problem-solving and critical-thinking skills. Nice to Have Experience working with Snowflake and large-scale data environments. Knowledge of NLP, deep learning, and AI-driven automation. Familiarity with Power BI for advanced data visualization. Physical Job Requirements The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position. Benefits & Compensation Medtronic offers a competitive Salary and flexible Benefits Package A commitment to our employees lives at the core of our values. We recognize their contributions. They share in the success they help to create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every career and life stage. About Medtronic We lead global healthcare technology and boldly attack the most challenging health problems facing humanity by searching out and finding solutions. Our Mission — to alleviate pain, restore health, and extend life — unites a global team of 95,000+ passionate people. We are engineers at heart— putting ambitious ideas to work to generate real solutions for real people. From the R&D lab, to the factory floor, to the conference room, every one of us experiments, creates, builds, improves and solves. We have the talent, diverse perspectives, and guts to engineer the extraordinary.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. The Defender Experts (DEX) Research team is at the forefront of Microsoft’s threat protection strategy, combining world-class hunting expertise with AI-driven analytics to protect customers from advanced cyberattacks. Our mission is to move protection left—disrupting threats early, before damage occurs—by transforming raw signals into intelligence that powers detection, disruption, and customer trust. We’re looking for a passionate and curious Data Scientist to join this high-impact team. In this role, you'll partner with researchers, hunters, and detection engineers to explore attacker behavior, operationalize entity graphs, and develop statistical and ML-driven models that enhance DEX’s detection efficacy. Your work will directly feed into real-time protections used by thousands of enterprises and shape the future of Microsoft Security. This is an opportunity to work on problems that matter—with cutting-edge data, a highly collaborative team, and the scale of Microsoft behind you. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Design and build robust, large-scale graph structures to model security entities, behaviors, and relationships. Develop and deploy scalable, production-grade AI/ML systems and intelligent agents for real-time threat detection, classification, and response. Collaborate closely with Security Research teams to integrate domain knowledge into data science workflows and enrich model development. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Work with large-scale graph data: create, query, and process it efficiently to extract insights and power models. Lead initiatives involving Graph ML, Generative AI, and agent-based systems, driving innovation across threat detection, risk propagation, and incident response. Collaborate closely with engineering and product teams to integrate solutions into production platforms. Mentor junior team members and contribute to strategic decisions around model architecture, evaluation, and deployment. Qualifications Bachelor’s or Master’s degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related quantitative field 6+ years of experience applying data science or machine learning in a real-world setting, preferably in security, fraud, risk, or anomaly detection Proficiency in Python and/or R, with hands-on experience in data manipulation (e.g., Pandas, NumPy), modeling (e.g., scikit-learn, XGBoost), and visualization (e.g., matplotlib, seaborn) Strong foundation in statistics, probability, and applied machine learning techniques Experience working with large-scale datasets, telemetry, or graph-structured data Ability to clearly communicate technical insights and influence cross-disciplinary teams Demonstrated ability to work independently, take ownership of problems, and drive solutions end-to-end Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Job Summary: We are seeking a highly skilled and experienced Data Scientist with a deep understanding of data analytics powered by artificial intelligence (AI) tools. The ideal candidate will be passionate about turning data into actionable insights using cutting-edge AI platforms, automation techniques, and advanced statistical methods. Key Responsibilities: Develop and deploy scalable AI-powered data analytics solutions for business intelligence, forecasting, and optimization. Leverage AI tools to automate data cleansing, feature engineering, model building, and visualization. Design and conduct advanced statistical analyses and machine learning models (supervised, unsupervised, NLP, etc.). Collaborate cross-functionally with engineering and business teams to drive data-first decision-making. Must-Have Skills & Qualifications: Minimum 4 years of professional experience in data science, analytics, or a related field. Proficiency in Python and/or R with strong hands-on experience in ML libraries (scikit-learn, XGBoost, TensorFlow, etc.). Expert knowledge of SQL and working with relational databases. Proven experience with data wrangling, data pipelines, and ETL processes. Deep Understanding of AI Tools for Data Analytics (Experience with several of the following is required): Data Preparation & Automation: Alteryx, Trifacta, KNIME AI/ML Platforms: DataRobot, H2O.ai, Amazon SageMaker, Azure ML Studio, Google Vertex AI Visualization & BI: Tableau, Power BI, Looker (with AI/ML integrations) AutoML & Predictive Modeling: Google AutoML, IBM Watson Studio, BigML NLP & Text Analytics: OpenAI (ChatGPT, Codex APIs), Hugging Face Transformers, MonkeyLearn Workflow Orchestration: Apache Airflow, Prefect Preferred Qualifications: Degree in Computer Science, Data Science, Statistics, or related field. Experience in cloud-based environments (AWS, GCP, Azure) for ML workloads. To apply, please send your resume to sooraj@superpe.in or shreya@superpe.in SuperPe is an equal opportunity employer and welcomes candidates of all backgrounds to apply. We look forward to hearing from you! Show more Show less

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: Manager- GBS Commercial Location: Bangalore Reporting to: Senior Manager - GBS Commercial 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., Causal Forests, 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. Technical Skills - Must Have 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 Power BI, Advanced MS Excel (Pivots, calculated fields, Conditional formatting, charts, dropdown lists, etc.), MS PowerPoint SQL & Python. Business Environment 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: Global 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. Previous Work Experience 5-8 years of experience in the Retail/CPG domain. Extensive experience solving business problems using quantitative approaches. Comfort with extracting, manipulating, and analyzing complex, high volume, high dimensionality data from varying sources. And above all of this, an undying love for beer! We dream big to create future with more cheer. Show more Show less

Job Information Date Opened 06/17/2025 Industry AEC Job Type Permanent Work Experience 1 - 3 Years City Mumbai State/Province Maharashtra Country India Zip/Postal Code 400093 About Us Axium Global (formerly XS CAD), established in 2002, is a UK-based MEP (M&E) and architectural design and BIM Information Technology Enabled Services (ITES) provider with an ISO 9001:2015 and ISO 27001:2022 certified Global Delivery Centre in Mumbai, India. With additional presence in the USA, Australia and UAE, our global reach allows us to provide services to customers with the added benefit of local knowledge and expertise. Axium Global is established as one of the leading pre-construction planning services companies in the UK and India, serving the building services (MEP), retail, homebuilder, architectural and construction sectors with high-quality MEP engineering design and BIM solutions. Job Description We are looking for a motivated and analytical Data Scientist with 2–4 years of experience to join our growing data team. The ideal candidate should be comfortable working with large datasets, building predictive models and generating actionable insights. Experience or familiarity with the AEC industry is a strong plus, as the role involves working on data generated from engineering, construction and design workflows. As a Data Scientist, you will play a key role in turning raw data into insights that support strategic decision-making. You will collaborate with cross-functional teams including software developers and domain experts. Your analytical models and tools will help enhance project performance, reduce risk and drive operational efficiency. Key Roles and Responsibilities: Analyze large datasets to identify trends, patterns and actionable insights Design and implement machine learning and neural network models for predictions, classifications and clustering Collaborate with AEC domain teams to understand data requirements and propose technical solutions Clean, transform, and validate data using SQL, Python Support automation of machine learning (ML) workflows and model reporting pipelines Document data science processes and results for transparency and reproducibility Create dashboards and visualizations using tools like Power BI, Tableau or Plotly Qualifications and Experience Required: BE/BTech/MTech degree in computer science, Data Science, Engineering, Statistics or a related field 2–4 years of hands-on experience in a Data Science or related role Strong programming skills in Python, and proficiency with SQL Experience with data science libraries (e.g pytorch, scikit-learn, pandas, NumPy, TensorFlow, XGBoost) Clarity with the concepts of Object-Oriented Programming (OOPs) Good understanding of statistics, machine learning techniques and data modeling Experience with data visualization tools such as Power BI, Tableau or Matplotlib Familiarity with the AEC industry and tools like Revit, Navisworks, BIM 360 or project scheduling data is a plus Strong communication skills and ability to present data findings to non-technical stakeholders Compensation: The selected candidate will receive competitive compensation and remuneration policies in line with qualifications and experience. Compensation will not be a constraint for the right candidate. What We Offer: A fulfilling working environment that is respectful and ethical A stable and progressive career opportunity State-of-the-art office infrastructure with the latest hardware and software for professional growth In-house, internationally certified training division and innovation team focusing on training and learning the latest tools and trends. Culture of discussing and implementing a planned career growth path with team leaders Transparent fixed and variable compensation policies based on team and individual performances, ensuring a productive association.

About The Role We're looking for a Senior Data Scientist with hands-on experience in machine learning, GenAI, and cloud platforms to solve real-world problems in the BFSI/Insurance space. You'll work with a collaborative team to build and deploy models that drive business impact - from fraud detection and churn prediction to customer segmentation and unstructured data analysis. What You'll Do Build ML models (XGBoost, Neural Networks, Random Forests) for classification, regression, anomaly detection, and more. Use unsupervised learning techniques for segmentation, clustering, and cohort creation. Apply LLMs and GenAI for insights from unstructured data (e.g., call transcripts, agent notes). Deploy solutions on cloud platforms (preferably AWS) using tools like Databricks, SageMaker, Lambda, Docker, etc. Implement MLOps best practices - versioning, CI/CD, monitoring. Collaborate with business teams to translate models into insights that matter. What You Bring 5+ years of experience in data science roles. 1-2 years working in BFSI or Insurance domain. Proficient in Python, SQL, Databricks. Strong understanding of ML fundamentals including optimization techniques like gradient descent. Experience with GenAI/LLMs (nice to have). Cloud experience (AWS preferred) with exposure to end-to-end model deployment. Great communication skills and a problem-solving mindset. (ref:hirist.tech) Show more Show less

Job Description: Data Scientist Role Overview The Data Scientist will lead the development of claims segmentation and forecasting models to support optimal adjuster planning. The role requires strong statistical and machine learning expertise, with a focus on applying data-driven insights to improve operational efficiency in claims management. Key Responsibilities Collaborate with business stakeholders to define claim complexity criteria. Develop and validate segmentation models to categorize claims into low, medium, and high-touch segments. Build forecasting models to predict claim volumes across complexity levels using historical claims data. Conduct feature engineering, model testing, and performance tuning. Translate model outputs into actionable business insights and support integration with capacity planning workflows. Document model methodology, assumptions, and deliverables. Work closely with the Data Engineer to ensure data readiness and pipeline efficiency. Skills & Experience 5+ years of experience in data science or analytics roles. Proficiency in Python (Pandas, Scikit-learn, XGBoost, etc.), SQL, and data visualization tools. Strong understanding of supervised learning, time-series forecasting, and model evaluation techniques. Experience working with operational or insurance claims data is preferred. Effective communication and stakeholder engagement skills. Show more Show less