38 Decision Trees Jobs

As a Machine Learning Engineer, you will play a key role in developing and enhancing a Telecom Artificial Intelligence Product. This role requires a strong background in machine learning and deep learning, along with extensive experience in implementing advanced algorithms and models to solve complex problems. You will be working on cutting-edge technologies to develop solutions for anomaly detection, forecasting, event correlation, and fraud detection. Your responsibilities will include developing production-ready implementations of proposed solutions using various machine learning and deep learning algorithms. You will test these solutions on live customer data to ensure efficacy and robustness. Additionally, you will research and test novel machine learning approaches for large-scale distributed computing applications. In this role, you will be responsible for implementing and managing the full machine learning operations lifecycle using tools such as Kubeflow, MLflow, AutoML, and Kserve for model deployment. You will develop and deploy machine learning models using PyTorch and TensorFlow to ensure high performance and scalability. Furthermore, you will run and manage PySpark and Kafka on distributed systems with large-scale, non-linear network elements. To excel in this position, you should be proficient in Python programming and experienced with machine learning libraries such as Scikit-Learn and NumPy. Experience in time series analysis, data mining, text mining, and creating data architectures will be beneficial. You should also be able to utilize batch processing and incremental approaches to manage and analyze large datasets. As a Machine Learning Engineer, you will experiment with multiple algorithms, optimizing hyperparameters to identify the best-performing models. You will execute machine learning algorithms in cloud environments, leveraging cloud resources effectively. Continuous feedback gathering, model retraining, and updating will be essential to maintain and improve model performance. Moreover, you should have expertise in network characteristics, transformer architectures, GAN AI techniques, and end-to-end machine learning projects. Experience with leading supervised and unsupervised machine learning methods and familiarity with Python packages like Pandas, Numpy, and DL frameworks like Keras, TensorFlow, PyTorch are required. Knowledge of Big Data tools and environments, as well as MySQL/NoSQL databases, will be advantageous. You will collaborate with cross-functional teams of data scientists, software engineers, and stakeholders to integrate implemented systems into the SaaS platform. Your innovative thinking and creative ideas will contribute to improving the overall platform. Additionally, you will create use cases specific to the domain to solve business problems effectively. Ideally, you should have a Bachelor's degree in Science/IT/Computing or equivalent with at least 4 years of experience in a QA Engineering role. Strong quantitative and applied mathematical skills are essential, along with certification courses in Data Science/ML. In-depth knowledge of statistical techniques, machine learning techniques, and experience with Telecom Product development are preferred. Experience in MLOps is a plus for deploying developed models, and familiarity with scalable SaaS platforms is advantageous for this role.,

Genpact (NYSE: G) is a global professional services and solutions firm dedicated to shaping the future by delivering impactful outcomes. With a team of over 125,000 professionals spread across more than 30 countries, we are characterized by our inherent curiosity, entrepreneurial spirit, and commitment to creating enduring value for our clients. Fueled by our overarching purpose of continually striving towards a world that functions better for individuals, we partner with and enhance leading enterprises, including members of the prestigious Fortune Global 500. Our core competencies revolve around in-depth business and industry expertise, digital operational services, and proficiency in data, technology, and AI. We are currently seeking applications for the position of Business Analyst - Data Scientist to join our dynamic team. As a Business Analyst - Data Scientist at Genpact, you will play a pivotal role in the development and implementation of NLP (Natural Language Processing) models and algorithms, extracting actionable insights from textual data, and collaborating with cross-functional teams to deliver innovative AI solutions. **Responsibilities:** **Model Development:** - Proficiency in various statistical, machine learning, and ensemble algorithms. - Strong understanding of time series algorithms and forecasting use cases. - Ability to discern the strengths and weaknesses of different models and select appropriate ones for specific problems. - Proficiency in evaluating metrics and recommending suitable evaluation metrics for different problem types. **Data Analysis:** - Extracting meaningful insights from structured data. - Preprocessing data for machine learning/artificial intelligence applications. **Collaboration:** - Close collaboration with data scientists, engineers, and business stakeholders. - Providing technical guidance and mentorship to team members. **Integration and Deployment:** - Integrating machine learning models into production systems. - Implementing CI/CD pipelines for continuous integration and deployment. **Documentation and Training:** - Documenting processes, models, and results. - Providing training and support to stakeholders on NLP techniques and tools. **Qualifications we seek in you:** **Minimum Qualifications / Skills:** - Bachelor's degree in computer science, engineering, or a related field. - Proficient programming skills in Python and R. - Experience with data science frameworks such as SKLEARN and NUMPY. - Knowledge of machine learning concepts and frameworks like TensorFlow and PyTorch. - Strong problem-solving and analytical capabilities. - Excellent communication and collaboration skills. **Preferred Qualifications/Skills:** - Experience in predictive analytics and machine learning techniques. - Proficiency in Python/R or any other open-source programming language. - Building and implementing models, using algorithms, and running simulations with various tools. - Familiarity with visualization tools such as Tableau, Power BI, Qlikview, etc. - Proficiency in applied statistics skills, including distributions, statistical testing, regression, etc. - Knowledge and experience in various tools and techniques like forecasting, linear regression, logistic regression, machine learning algorithms (e.g., Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning), etc. - Experience with big data technologies (Hadoop, Spark). - Familiarity with cloud platforms like AWS, Azure, GCP. **Job Details:** **Title:** Business Analyst - Data Scientist **Primary Location:** India-Hyderabad **Education Level:** Bachelor's / Graduation / Equivalent **Job Posting:** Apr 1, 2025, 2:47:23 AM **Unposting Date:** May 1, 2025, 1:29:00 PM **Master Skills List:** Digital **Job Category:** Full Time,

We are looking for an experienced AI/ML Architect to spearhead the design, development, and deployment of cutting-edge AI and machine learning systems. As the ideal candidate, you should possess a strong technical background in Python and data science libraries, profound expertise in AI and ML algorithms, and hands-on experience in crafting scalable AI solutions. This role demands a blend of technical acumen, leadership skills, and innovative thinking to enhance our AI capabilities. Your responsibilities will include identifying, cleaning, and summarizing complex datasets from various sources, developing Python/PySpark scripts for data processing and transformation, and applying advanced machine learning techniques like Bayesian methods and deep learning algorithms. You will design and fine-tune machine learning models, build efficient data pipelines, and leverage distributed databases and frameworks for large-scale data processing. In addition, you will lead the design and architecture of AI systems, with a focus on Retrieval-Augmented Generation (RAG) techniques and large language models. Your qualifications should encompass 5-7 years of total experience with 2-3 years in AI/ML, proficiency in Python and data science libraries, hands-on experience with PySpark scripting and AWS services, strong knowledge of Bayesian methods and time series forecasting, and expertise in machine learning algorithms and deep learning frameworks. You should also have experience in structured, unstructured, and semi-structured data, advanced knowledge of distributed databases, and familiarity with RAG systems and large language models for AI outputs. Strong collaboration, leadership, and mentorship skills are essential. Preferred qualifications include experience with Spark MLlib, SciPy, StatsModels, SAS, and R, a proven track record in developing RAG systems, and the ability to innovate and apply the latest AI techniques to real-world business challenges. Join our team at TechAhead, a global digital transformation company known for AI-first product design thinking and bespoke development solutions. With over 14 years of experience and partnerships with Fortune 500 companies, we are committed to driving digital innovation and delivering excellence. At TechAhead, you will be part of a dynamic team that values continuous learning, growth, and crafting tailored solutions for our clients. Together, let's shape the future of digital innovation worldwide!,

As a part of the Talent Acquisition team at Tesco, you will play a crucial role in representing Talent Acquisition in various forums and seminars related to process, compliance, and audit. Additionally, you will be responsible for driving a Continuous Improvement (CI) culture, implementing CI projects, and fostering innovation within the team. Your role will involve engaging with business and functional partners to gain a deep understanding of business priorities. You will be required to ask relevant questions and translate the insights into an analytical solution document. This document will highlight how the application of data science can enhance decision-making processes. To excel in this role, you must possess a strong understanding of techniques for preparing analytical data sets from multiple complex sources. You will be expected to develop statistical models and machine learning algorithms with a high level of competency. Furthermore, you will need to write structured, modularized, and codified algorithms using Continuous Improvement principles. In addition to building algorithms, you will create an easy-to-understand visualization layer on top of the analytical models. This visualization layer will empower end-users to make informed decisions. You will also be responsible for proactively promoting the adoption of solutions developed by the team and identifying areas for improvement within the larger Tesco business. Keeping abreast of the latest trends in data science and retail analytics is essential for this role. You will be expected to share your knowledge with colleagues and mentor a small team of Applied Data Scientists to deliver impactful analytics projects. Your responsibilities will include leading solution scoping and development to facilitate the collaboration between Enterprise Analytics teams and Business teams across Tesco. It is imperative to adhere to the Business Code of Conduct, act with integrity, and fulfill specific risk responsibilities related to Talent Acquisition, process compliance, and audit. To thrive in this role, you will need expertise in Applied Math, including Applied Statistics, Regression, Decision Trees, Forecasting, and Optimization algorithms. Proficiency in SQL, Hadoop, Spark, Python, Tableau, MS Excel, MS PowerPoint, and GitHub is also required. Additionally, having a basic understanding of the Retail domain and soft skills such as Analytical Thinking, Problem-solving, Storyboarding, and Stakeholder engagement will be beneficial. Joining Tesco's team in Bengaluru offers you the opportunity to be part of a multi-disciplinary team that aims to serve customers, communities, and the planet better each day. By standardizing processes, delivering cost savings, leveraging technological solutions, and empowering colleagues, Tesco in Bengaluru strives to create a sustainable competitive advantage. With a focus on reducing complexity and offering high-quality services, you will contribute to Tesco's mission of providing exceptional experiences for customers worldwide. Tesco Technology is a diverse team of over 5,000 experts located in various countries, including India. The Technology division encompasses roles in Engineering, Product Development, Programme Management, Service Desk Operations, Systems Engineering, Security & Capability, Data Science, and more. Established in 2004, Tesco in Bengaluru plays a vital role in enhancing customer experiences and streamlining operations for millions of customers and over 330,000 colleagues globally.,

As the Manager- Data Science at Holcim, you will play a crucial role in the Groups Global Advanced Analytics CoE by enabling our Businesses for Insights Driven Operations and Decision making through the utilization of cutting edge Analytics tools and techniques. Your primary responsibility will involve working closely with Business / Domain Subject Matter Experts to understand pain points and opportunities, and develop analytical models to identify patterns and predict outcomes of key business processes. You will be required to identify the most suitable modeling techniques and apply Machine Learning and Deep Learning Algorithms to create self-correcting models and algorithms. It will be essential to collaborate with Product Development teams to industrialize AI / ML models and conduct rapid and iterative prototyping of minimum viable solutions. Additionally, you will test hypotheses on raw datasets to derive meaningful insights and identify new opportunity areas. Your role will encompass all aspects of data including data acquisition, data exploration, feature engineering, building and optimizing models, and deploying Gen AI Solutions. You will be involved in designing full stack ML solutions in a distributed computing environment such as AWS and GCP, with the possibility of developing ML solutions for deployment on the edge or mobile devices if required. To be successful in this role, you should possess a total experience of 12-15 years with at least 8 years of relevant Analytics experience. Industry Experience and knowledge, particularly in Manufacturing/ Operations Functions within the Building Material Industry, Manufacturing, Process, or Pharma sectors, is preferred. Hands-on experience in statistical and data science techniques, as well as developing and deploying Gen AI Solutions, will be critical for this position. In terms of technical skills, you should have over 8 years of hands-on experience in advanced Machine Learning & Deep Learning techniques and algorithms, such as Decision Trees, Random Forests, SVMs, Regression, Clustering, Neural Networks, CNNs, RNNs, LSTMs, and Transformers. Proficiency in statistical computer languages like Python and PySpark to manipulate data and draw insights from large datasets is essential. Experience with Cloud platforms like AWS, DL frameworks such as TensorFlow, Keras, or PyTorch, and familiarity with business intelligence tools and data frameworks will be advantageous. In addition to technical skills, leadership and soft skills are equally important for this role. You should lead by example on values and culture, be open-minded, collaborative, and an effective team player. Working in a multicultural and diverse team, dealing with ambiguity, and communicating openly and effectively with various stakeholders are key aspects of this position. Being driven for success, aspiring to a culture of service excellence, and always prioritizing customer satisfaction, people, and business are qualities that will set you up for success in this role. If you are motivated by the opportunity to make a significant impact through data-driven decisions and innovative solutions, we invite you to build your future with us at Holcim by applying for this role.,

As the leader of the data analytics and AI team, you will play a crucial role in driving our organization towards a data-first and data-driven approach. Your primary responsibility will be to deliver and maintain smart data-driven solutions that are essential for our growth and daily operations. By accelerating the adoption of AI solutions, you will enhance efficiency, foster innovation, and gain a competitive advantage for the company. Your role will involve overseeing all aspects of new data and AI projects, from their inception to delivery, with a strong emphasis on assessing business value, ROI, and cost reduction. Your key responsibilities will include leading and developing a robust data analytics and AI team, establishing best practices and methodologies for data analytics and responsible AI initiatives, managing and overseeing AI and LLM projects, building relationships with business process owners, collaborating with internal and external stakeholders, developing advanced models and algorithms, addressing data mining performance issues, and staying updated on the latest advancements in AI and LLM technologies to improve project outcomes. Preferred skills for this role include proficiency in programming languages such as Python, R, or similar, understanding of algorithms like linear regression, logistic regression, decision trees, random forest, boosting algorithms (e.g., XGBoost), clustering techniques, and principal component analysis. Additionally, familiarity with data science concepts including statistics, probability, data transformation, visualization, storytelling, and deep learning, as well as expertise in statistical and mathematical methods and data & AI technologies/tools like ML Ops, ETL, data lakes, graph databases, NLK, and data optimization will be beneficial for success in this position.,

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

You are passionate about leveraging AI and data science to transform banking technology. Join Infosys Finacle and contribute to driving innovation in the financial services industry. You will work on cutting-edge AI solutions in collaboration with top industry leaders, proposing innovative solutions and adapting quickly in a dynamic learning environment. Your responsibilities will include building AI algorithms, designing experiments to manage and extract actionable insights from large data sets, and using predictive modeling to enhance customer experiences, optimize revenue, improve ad targeting, and achieve various business goals. You will also develop Explainable and Responsible AI models, conduct research to develop prototypes and proof of concepts, and identify opportunities to apply data science insights across different teams and functions. Your enthusiasm for solving complex problems with algorithms will inspire others in the team. You should have 2 to 10+ years of relevant experience in data science or analytics, along with strong analytical and problem-solving skills. Proficiency in statistical programming languages such as Python, SQL, etc., and in-depth knowledge of advanced statistical techniques like regression, distributions, and statistical tests are required. Experience with machine learning algorithms including regression, simulation, scenario analysis, modeling, clustering, decision trees, and neural networks is essential. You should also be able to deploy models as APIs and possess excellent communication and presentation skills to convey complex ideas to non-technical stakeholders. If you are ready to make an impact, you can email your CV and details to sweta.singh09@infosys.com. The interview process consists of 3 rounds - Online Coding Assessment (120 Mins), Technical Round, and Hiring Manager Round. Infosys Finacle offers you the opportunity to build core banking platforms used by global financial institutions, learn, grow, and innovate with the best minds in the industry, and be a part of a global digital banking transformation. Finacle, an industry leader in digital banking solutions, partners with emerging and established financial institutions to inspire better banking. Their cloud-native solution suite and SaaS services help banks engage, innovate, operate, and transform better. Finacle is a business unit of EdgeVerve Systems, a wholly-owned product subsidiary of Infosys, a global technology leader with over USD 15 billion in annual revenues. Known for their functionally rich solution suite, composable architecture, culture, and entrepreneurial spirit of a start-up, Finacle has an impeccable track record of helping financial institutions drive digital transformation at speed and scale. To learn more about Finacle, visit their website at https://www.edgeverve.com/finacle/solutions/. Disclaimer: Edgeverve Systems does not engage with external manpower agencies or charge any fees from candidates for recruitment. If you encounter such scams, please report them immediately.,

We are seeking engineers or applied scientists who have expertise in implementing data mining and machine learning systems to contribute to the development of an innovative online education platform that is tailored to the unique needs of each student. Your responsibilities will include: - Demonstrating a strong passion and enthusiasm for constructing scalable systems that can analyze extensive datasets and provide actionable insights. - Showcasing a proven track record of identifying connections within vast and seemingly unrelated datasets. - Displaying the ability to work with incomplete or imperfect data sets effectively. - Possessing knowledge of linear algebra and proficiency in manipulating data through matrix algorithms. - Having the capability to develop and interpret probabilistic models of intricate, multi-dimensional systems. - Demonstrating experience in quantitative analysis using Python. - Having familiarity with database technologies like SQL. - Showcasing solid programming skills in Java, C, C++, or Python. Preferred experience with the following technologies: - Collaborative filtering. - Decision trees and automatic tree generation. - Bayesian methods. - Clustering techniques including principal components analysis, k-means, etc. Desired qualifications include: - Proficiency in Hadoop or other MapReduce implementations. - Experience in semantic text mining or natural language processing. - Prior involvement in high-stakes information retrieval and statistical analysis, such as Bioinformatics or Fraud Detection. If you believe you meet these qualifications and are excited about this opportunity, please send your resume to info@zunopy.com.,

As a Data Science Instructor at our dynamic team, you will play a crucial role in preparing students for the evolving data science landscape. Your primary focus will be on delivering immersive and hands-on learning experiences to equip future data professionals with practical skills in SQL, Python, Machine Learning, and real-world project development. Your responsibilities will include developing and conducting engaging lessons and workshops covering core data science topics, with a notable emphasis on SQL and Python programming. You will guide students through foundational machine learning models such as linear regression, logistic regression, decision trees, and random forests, ensuring they comprehend both the theoretical concepts and practical applications. Moreover, you will be tasked with designing and facilitating hands-on projects to help students apply their knowledge effectively and build a robust portfolio of work. Your ability to explain complex technical concepts in a clear and concise manner will be pivotal in making the material accessible to a diverse group of learners. As a mentor, you will provide constructive feedback and guidance to support students in overcoming challenges and enhancing their understanding. Collaboration with our team to continuously enhance and refine our curriculum to ensure its relevance and cutting-edge nature will also be part of your role. To excel in this position, you must have proven experience as a Data Scientist, Machine Learning Engineer, or similar role, backed by a strong portfolio that demonstrates your expertise in Python and machine learning projects. Your proficiency in Python for data analysis, manipulation, and model building, along with practical experience in common machine learning models, is essential. Additionally, your exceptional ability to design and lead hands-on projects that foster practical skill development, coupled with strong communication and presentation skills, will be key in your success. Proficiency in SQL for data querying and management is also required. Preferred qualifications include familiarity with Python libraries like Streamlit, experience with Natural Language Processing (NLP) concepts, exposure to Large Language Models (LLMs) or chatbot development, and prior experience in teaching, mentoring, or training roles. If you are enthusiastic about empowering the next generation of data scientists and possess a proven track record in building and explaining data science projects, we encourage you to reach out to us at hr@ndmit.com. Join us in shaping the future of data science education!,

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

As an Associate Economics Analyst at Mastercard Economics Institute (MEI) in North America (NAM), you will play a crucial role in supporting the lab's mission of driving economic thought leadership to foster a more inclusive and sustainable digital economy. Established in 2020, MEI focuses on analyzing economic trends from a consumer perspective to provide customized insights on economic issues for customers, partners, and policymakers. The team, comprising economists and data scientists, leverages anonymized and aggregated data from the Mastercard network along with public data to deliver impactful insights through various channels such as presentations, global leadership, media engagement, and commercial projects using the company's product offerings. Your responsibilities will include collaborating with stakeholders across NAM, engaging with external clients, academic institutions, and industry partners, and conducting economic research and data analytics for the European region under the guidance of the Vice President, Lead Economist, NAM. You will be involved in hypothesis development at the intersection of economics and retail, creating proprietary diagnostic indices from large datasets, and deriving actionable insights to enhance existing products and develop new solutions. Additionally, you will contribute to thought leadership activities by sharing knowledge, best practices, and supporting new solution development in the realm of economic research related to retail and commerce. To excel in this role, you should hold a Bachelor's degree in Economics (preferred), Statistics, or Mathematics, with proficiency in SQL and data visualizations. Critical thinking, problem-solving skills, and a strong willingness to learn are essential qualities. Expertise in programming languages like R, Python, or similar, along with experience in data visualization tools such as Tableau or Power BI, will be beneficial. Familiarity with JavaScript for visualization and proficiency in key econometric and statistical techniques will be advantageous for this position. Moreover, as a member of the Mastercard team, it is imperative that you adhere to the organization's security policies, maintain the confidentiality and integrity of accessed information, report any security breaches, and undergo mandatory security training periodically to uphold information security standards. If you are passionate about economics, data analytics, and contributing to a more sustainable digital economy, this role offers a unique opportunity to make a meaningful impact by leveraging your skills and expertise at MEI in North America (NAM).,

As a Senior ML Scientist in the Advertising Optimization & Automation Science team at Wayfair, you will play a crucial role in leveraging machine learning and generative AI to streamline campaign workflows. Based in Bangalore, India, you will contribute to building intelligent systems that drive personalized recommendations and campaign automation within Wayfair's advertising platform. Your responsibilities will include designing and implementing intelligent budget, tROAS, and SKU recommendations, as well as simulation-driven decisioning to enhance advertiser outcomes and unlock substantial commercial value. In collaboration with cross-functional teams, you will lead the development of GenAI-powered creative optimization and automation to drive incremental ad revenue and improve supplier outcomes. Additionally, you will elevate technical standards by promoting best practices in ML system design and development across the team. The ideal candidate for this role possesses a Bachelor's or Masters degree in Computer Science, Mathematics, Statistics, or a related field, along with 9+ years of experience in building large-scale machine learning algorithms. You should have a strong theoretical understanding of statistical models and ML algorithms, proficiency in programming languages such as Python, and experience with relevant ML libraries like TensorFlow and PyTorch. Strategic thinking, customer-centric mindset, and a desire for creative problem-solving are essential qualities for success in this position. Additionally, you should be adept at influencing senior-level stakeholders, possess excellent communication skills, and demonstrate the ability to shape technical roadmaps through cross-functional partnerships. Nice-to-have qualifications include experience with GCP, Airflow, and containerization, as well as familiarity with Generative AI and agentic workflows. Knowledge of Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning is also advantageous. By joining Wayfair, you will be part of a dynamic and innovative team that is dedicated to reinventing the way people shop for their homes. If you are looking for a fast-paced environment that offers continuous learning and growth opportunities, Wayfair may be the perfect place for you to advance your career.,

As an Application Developer, you will design, build, and configure applications to meet business process and application requirements. Your responsibilities include ensuring the smooth functioning of applications, addressing any arising issues, collaborating with the team, making team decisions, and engaging with multiple teams. Your problem-solving abilities and expertise in SAP Global Trade Services will be crucial in contributing to the success of the project. You are expected to be a Subject Matter Expert (SME) and manage the team to perform effectively. Your role involves making team decisions, contributing to key decisions, providing solutions to problems within and across multiple teams, and ensuring the applications" smooth operation. Proficiency in SAP Global Trade Services, statistical analysis, machine learning algorithms, data visualization tools like Tableau or Power BI, and hands-on experience with various machine learning algorithms are essential. Additionally, you should have a strong grasp of data munging techniques to maintain data quality and integrity. The ideal candidate should possess a minimum of 7.5 years of experience in SAP Global Trade Services. This full-time position is based in Hyderabad and requires a 15 years full-time education.,

The Staff ML Scientist position at Visa offers a unique opportunity to engage in cutting-edge Applied AI research within the realm of data analytics. As a key member of the team, you will play a pivotal role in driving Visa's strategic vision as a leading data-driven company. Your responsibilities will involve formulating complex business problems into technical data challenges, collaborating closely with product stakeholders to ensure the practicality of solutions, and delivering impactful prototypes and production code. You will have the chance to experiment with various datasets, both in-house and third-party, to evaluate their relevance to business objectives. Moreover, your role will encompass building data transformations for structured and unstructured data, exploring and refining modeling and scoring algorithms, and implementing methods for adaptive learning and model validation. Your expertise in automation and predictive analytics will be instrumental in enhancing operational efficiency and performance monitoring. In addition to your technical skills, you will be expected to possess a strong academic background and exceptional software engineering capabilities. A proactive and detail-oriented approach, coupled with excellent collaboration skills, will be essential for success in this role. This is a hybrid position, allowing for a flexible work arrangement that combines remote work and office presence. The expectation is to work from the office 2-3 set days per week, with a general guideline of being in the office at least 50% of the time based on business requirements. Qualifications: - 8 or more years of work experience with a Bachelors Degree or an Advanced Degree - Proficiency in modeling techniques such as logistic regression, Nave Bayes, SVM, decision trees, or neural networks - Ability to program in scripting languages like Perl or Python, and programming languages such as Java, C++, or C# - Familiarity with statistical tools like SAS, R, KNIME, and experience with deep learning frameworks like TensorFlow - Knowledge of Natural Language Processing and working with large datasets using tools such as Hadoop, MapReduce, Pig, or Hive - Publications or presentations in recognized Machine Learning and Data Mining journals/conferences would be advantageous Join Visa as a Staff ML Scientist and contribute to pioneering advancements in Applied AI research that drive innovation and shape the future of data analytics.,

You will be joining KPMG in India, a professional services firm affiliated with KPMG International Limited since its establishment in August 1993. Leveraging a global network of firms, we provide services to national and international clients across various sectors with offices in multiple cities across India. As part of the Financial Crimes specialist team, your role will involve providing solutions to BFSI clients through model validation testing for AML risk models and frameworks, sanctions screening, and transaction monitoring systems. We are seeking individuals with advanced data science and analytics skills to support our team in addressing the challenges associated with financial crime. Your responsibilities will include but are not limited to supporting functional SME teams in building data-driven Financial Crimes solutions, conducting statistical testing of screening matching algorithms and risk rating models, validating data models of AML systems, and developing AML models to detect suspicious activities and transactions. You will collaborate with cross-functional teams to analyze data for model development and validation, prepare detailed documentation and reports, and assist in feature engineering for automation of AML-related investigations. To qualify for this role, you should have a Bachelor's degree from an accredited university, at least 3 years of hands-on experience in Python with knowledge of frameworks like Java, Fast, Django, Tornado, or Flask, experience with Relational and NoSQL databases, proficiency in BI tools such as Power BI and Tableau, and an educational background in Data Science and Statistics. Additionally, expertise in machine learning algorithms, statistical analysis, and familiarity with regulatory guidelines for AML compliance are essential. Preferred qualifications include experience in AML model validation, statistical testing of risk models, and familiarity with AML technology platforms. Hands-on experience with data analytics tools like Informatica and Kafka is also desirable. If you are looking to contribute your advanced analytics skills to combat financial crime and support leading financial institutions in adhering to industry best practices, this role offers you the opportunity to work on challenging projects and develop professionally in a dynamic environment.,

You will be responsible for building and interpreting machine learning models on real business data from the SigView platform, such as Logistic Regression, Boosted trees (Gradient boosting), Random Forests, and Decision Trees. Your tasks will include identifying data sources, integrating multiple sources or types of data, and applying data analytics expertise within a data source to develop methods to compensate for limitations and extend the applicability of the data. Moreover, you will be expected to extract data from relevant data sources, including internal systems and third-party data sources, through manual and automated web scrapping. Your role will involve validating third-party metrics by cross-referencing various syndicated data sources and determining the numerical variables to be used in the same form as they are from the raw datasets, categorized into buckets, and used to create new calculated numerical variables. You will perform exploratory data analysis using PySpark to finalize the list of compulsory variables necessary to solve the business problem and transform formulated problems into implementation plans for experiments by applying appropriate data science methods, algorithms, and tools. Additionally, you will work with offshore teams post data preparation to identify the best statistical model/analytical solution that can be applied to the available data to solve the business problem and derive actionable insights. Your responsibilities will also include collating the results of the models, preparing detailed technical reports showcasing how the models can be used and modified for different scenarios in the future to develop predictive insights. You will develop multiple reports to facilitate the generation of various business scenarios and provide features for users to generate scenarios. Furthermore, you will be interpreting the results of tests and analyses to develop insights into formulated problems within the business/customer context and provide guidance on risks and limitations. Acquiring and using broad knowledge of innovative data analytics methods, algorithms, and tools, including Spark, Elasticsearch, Python, Databricks, Azure, Power BI, Azure Cloud services, LLMs-Gen AI, and Microsoft Suite will be crucial for success in this role. This position may involve telecommuting and requires 10% travel nationally to meet with clients. The minimum requirements for this role include a Bachelor's Degree in Electronics Engineering, Computer Engineering, Data Analytics, Computer Science, or a related field plus five (5) years of progressive experience in the job offered or related occupation. Special skill requirements for this role include applying statistical methods to validate results and support strategic decisions, building and interpreting advanced machine learning models, using various tools such as Python, Scikit-Learn, XGBoost, Databricks, Excel, and Azure Machine Learning for data preparation and model validation, integrating diverse data sources using data analytics techniques, and performing data analysis and predictive model development using AI/ML algorithms. Your mathematical knowledge in Statistics, Probability, Differentiation and Integration, Linear Algebra, and Geometry will be beneficial. Familiarity with Data Science libraries such as NumPy, SciPy, and Pandas, Azure Data Factory for data pipeline design, NLTK, Spacy, Hugging Face Transformers, Azure Text Analytics, OpenAI, Word2Vec, and BERT will also be advantageous. The base salary for this position ranges from $171,000 to $190,000 per annum for 40 hours per week, Monday to Friday. If you have any applications, comments, or questions regarding the job opportunity described, please contact Piyush Khemka, VP, Business Operations, at 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310.,

The Economic Analyst, North America (NAM) position at Mastercard Economics Institute (MEI) involves engaging in data analytics and economic research for the U.S. and Canada. Reporting to the VP, Lead Economist for North America at MEI, you will be responsible for supporting client and stakeholder engagements, collaborating with external clients and partners, and generating initial insights to create impactful storylines and visuals. You will also be involved in synthesizing analyses into clear recommendations, writing reports and client presentations, enhancing existing products, and proactively seeking new knowledge to improve productivity. The role requires a Bachelor's degree in Economics, Statistics, or Mathematics, with experience in statistical modeling, quantitative analysis, and R development, focusing on economic research. Proficiency in SQL and Hadoop is essential, along with expertise in R, Python, or other statistical packages. Experience with Tableau is preferred, and knowledge of JavaScript for data visualization is a plus. Familiarity with econometric and statistical techniques such as predictive modeling, regression analysis, time series modeling, and data mining methods is necessary. A willingness to learn additional statistical applications and software is expected. Candidates with prior experience in the financial services industry will be given preference. Strong communication and writing skills are essential for this role, along with the ability to actively participate in thought leadership activities and contribute to the continuous improvement of quality and productivity within the organization.,

As an IT Service Management Representative, you will oversee the delivery of IT production systems and services, supporting the infrastructure service management lifecycle to ensure client satisfaction and manage service risks. Your role involves providing operational support to keep production systems and devices online and available. Expected to perform independently and become a Subject Matter Expert (SME), you will actively participate and contribute in team discussions, providing solutions to work-related problems. Your responsibilities include managing delivery for IT production systems and services, supporting the infrastructure service management lifecycle, ensuring client satisfaction, and managing risk to services. Additionally, you will collaborate with team members to troubleshoot and resolve issues. Required professional and technical skills include proficiency in Reporting Analytics, a strong understanding of statistical analysis and machine learning algorithms, experience with data visualization tools like Tableau or Power BI, and hands-on experience in implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. You should also have a solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Candidates should possess a minimum of 3 years of experience in Reporting Analytics. This position is based at our Nagpur office, and a 15 years full-time education is required.,

As a Data Platform Engineer, you will assist with the data platform blueprint and design, encompassing the relevant data platform components. You will collaborate with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Your typical day will involve working on the data platform blueprint and design, collaborating with architects, and ensuring seamless integration between systems and data models. Expected to perform independently and become an SME, you will actively participate/contribute in team discussions and provide solutions to work-related problems. Your responsibilities will include assisting with the data platform blueprint and design, collaborating with Integration Architects and Data Architects, ensuring cohesive integration between systems and data models, implementing data platform components, and troubleshooting and resolving data platform issues. In terms of professional & technical skills, proficiency in Databricks Unified Data Analytics Platform is a must-have. You should have a strong understanding of statistical analysis and machine learning algorithms, experience with data visualization tools like Tableau or Power BI, and hands-on experience implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Furthermore, a solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity, is essential. The candidate for this position should have a minimum of 3 years of experience in Databricks Unified Data Analytics Platform. This position is based at the Bengaluru office and requires a 15 years full-time education.,

As a Data Scientist Associate Manager at SC&O - S&P I&F Decision Science, you will play a crucial role in leading the design, development, and implementation of AI/ML-powered procurement and analytics solutions. Your responsibilities will involve collaborating with cross-functional teams to create platforms that identify cost-saving opportunities, improve supplier management, and provide valuable business intelligence to enterprise clients. One of your key duties will be to analyze procurement spend using various techniques to classify it into a custom taxonomy within Accenture's spend analytics tool. You will also be involved in collecting data from different sources through interactions with stakeholders and conducting data quality assessments. Additionally, you will assist in creating data cleansing rules and incorporating data clarifications from source owners. To excel in this role, you should have hands-on experience with Python, including threading limitations and multi-process architecture. Proficiency in MySQL to integrate multiple data sources is essential. Strong coding skills in languages such as R, SQL, JavaScript, Java, CSS, and C++ will be beneficial. Familiarity with statistical and data mining techniques, along with advanced machine learning algorithms and statistics, is also required. Ideal candidates for this position should possess 6-12 years of experience in data modeling, ETL automation, AI/ML, and front-end design. A background in handling and classifying spend data using AI/ML techniques is highly desirable. Strong leadership, team management, proficiency in MS Excel and MS PowerPoint, attention to detail, accuracy, and innovative problem-solving skills are crucial for success in this role. Previous experience in supply chain management and applying AI/ML techniques to optimize operations is preferred. Join us at Accenture and be part of a dynamic team driving innovation and excellence in decision science and data analytics.,

Wayfair's Advertising business is expanding rapidly, contributing significant profits to the company. The team is focused on building Sponsored Products, Display & Video Ad offerings to meet various Advertiser goals and deliver highly relevant Ads to millions of customers. The Ads Platform is evolving to empower advertisers of all sophistication levels to achieve a strong ROI through state-of-the-art Machine Learning techniques. The Advertising Optimization & Automation Science team plays a crucial role in this expansion. Leveraging machine learning and generative AI, the team streamlines campaign workflows and provides impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Intelligent systems for creative optimization and agentic frameworks are also being developed to simplify and enhance advertiser interactions. As a Machine Learning Scientist in the Advertising Optimization & Automation Science team, you will be responsible for developing budget, tROAS, and SKU recommendations, and other machine learning capabilities to support the ads business. Collaborating with other scientists, as well as Product and Engineering teams, you will apply your engineering and machine learning skills to tackle impactful and intellectually challenging problems that directly impact Wayfair's revenue. Responsibilities: - Design, build, deploy, and refine large-scale machine learning models and algorithmic decision-making systems to address real-world problems for customers. - Collaborate with commercial stakeholders to understand business challenges and opportunities, developing analytical solutions accordingly. - Work closely with engineering, infrastructure, and machine learning platform teams to ensure best practices in building and deploying scalable machine learning services. - Identify new opportunities and insights from data to improve models and project the ROI of proposed modifications. - Maintain a customer-centric approach in framing, approaching, and solving every problem. Requirements: - 3+ years of industry experience with a Bachelor/Masters degree or 1-2 years of industry experience with a PhD in Computer Science, Mathematics, Statistics, or related field. - Proficiency in Python or another high-level programming language. - Hands-on experience deploying machine learning solutions into production. - Strong theoretical understanding of statistical models like regression, clustering, and machine learning algorithms such as decision trees and neural networks. - Excellent written and verbal communication skills. - Intellectual curiosity and a passion for continuous learning. Nice to have: - Experience with Python machine learning ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML). - Familiarity with GCP (or AWS, Azure), machine learning model development frameworks, and machine learning orchestration tools like Airflow, Kubeflow, or MLFlow. - Experience in information retrieval, query/intent understanding, search ranking, recommender systems, etc. - Familiarity with deep learning frameworks like PyTorch, Tensorflow, etc.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. Your unique voice and perspective are valued to help EY become even better. Join us and contribute to building an exceptional experience for yourself and creating a better working world for all. As a part of our EY - Technology Risk team, you will contribute technically to IT Risk and Assurance client engagements as well as internal projects. Your role will involve actively establishing, maintaining, and strengthening internal and external relationships. You will also be responsible for identifying potential business opportunities for Ernst & Young within existing engagements and escalating them as appropriate. Anticipating and identifying risks within engagements and sharing any issues with senior team members will also be part of your responsibilities. The opportunity entails helping clients navigate the complex world of modern data science and analytics. You will provide advice to clients on designing, implementing, stabilizing, and optimizing internal controls using cutting-edge and scalable AI & Big Data technologies. Your key responsibilities include: - Building and leveraging cutting-edge Gen AI & Big Data platforms to deliver insights for comprehensive Risk & Controls monitoring mechanisms. - Creating executive reporting, proposals, and marketing material with the highest quality deliverables. - Collaborating within the team to solve technical challenges in the design and development of the next-generation AI & Data-led Risk technology platform. To qualify for this role, you must have: - 4+ years of working experience in Large Scale AI/ML models and data science. - Deep understanding of statistics, AI/ML algorithms, and predictive modeling. - Proficiency in AI/ML programming languages like Python, R, and SQL. - Expertise in machine learning algorithms and data mining techniques including deep learning algorithms. - Strong programming skills in Python with machine learning libraries such as Scikit-learn, Pandas, NumPy, etc. - Knowledge of tools such as Docker, Kubernetes, Git, and deep learning frameworks like TensorFlow, PyTorch, or Keras. Ideally, you'll also have a Bachelor's Degree or above in mathematics, information systems, statistics, computer science, Data Science, or related disciplines. Relevant certifications are considered a plus. Being self-driven, a creative problem solver, and enjoying the fast-paced environment of software development are qualities that are valued. At EY, you will have opportunities to work with leading businesses globally and develop your skills and career. You will work on inspiring and meaningful projects, receive support, coaching, and feedback from engaging colleagues, and have the freedom and flexibility to handle your role in a way that suits you. EY is committed to building a better working world by creating long-term value for clients, people, and society through trust, data, and technology.,

As an Economic Analyst for North America (NAM) at the Mastercard Economics Institute (MEI), you will play a crucial role in contributing to economic research and data analytics for the U.S. and Canada. Reporting directly to the VP, Lead Economist for North America, you will be responsible for engaging in client and stakeholder interactions, collaborating with external partners, and generating actionable insights to support impactful economic storylines and visuals. Your role will involve synthesizing analyses into clear recommendations, assisting in the creation of reports and client presentations, and enhancing existing products while also contributing to the development of new solutions. You will be expected to proactively seek new knowledge, structure project work efficiently, and actively participate in thought leadership activities to continuously improve the quality and productivity of economic research initiatives. To excel in this role, you must hold a Bachelor's degree in Economics, Statistics, or Mathematics, with a strong background in statistical modeling, quantitative analysis, and data engineering, particularly in economic research. Proficiency in SQL and Hadoop is essential, along with expertise in statistical packages such as R, Python, and Tableau. Knowledge of JavaScript for data visualization is advantageous, and experience in financial services would be beneficial. In addition to technical skills, excellent communication and strong writing abilities are required for effective collaboration and presentation of insights. You should be willing to learn new statistical applications or software as needed and demonstrate proficiency in key econometric and statistical techniques to support the Institute's mission to provide valuable economic insights for customers, partners, and policymakers.,

As a Data Scientist Associate Manager in the SC&O - S&P I&F Decision Science team at Accenture, you will play a crucial role in leading the design, development, and implementation of AI/ML-powered procurement and analytics solutions. Your responsibilities will involve collaborating with cross-functional teams to create platforms that drive cost-saving opportunities, improve supplier management, and provide valuable business intelligence to our enterprise clients. Your primary roles and responsibilities will include analyzing procurement spend through various techniques to classify it into a custom taxonomy within Accenture's spend analytics tool. You will also be involved in collecting data from different sources during calls with stakeholders, leading data quality assessments, identifying gaps, and creating summaries as per database requirements. Additionally, you will assist in data scrubbing by developing data cleansing rules and incorporating data clarifications provided by data source owners. To excel in this role, you should have hands-on experience in Python with threading limitations and multi-process architecture. Proficiency in MySQL to integrate multiple data sources is also essential. Furthermore, you should possess strong coding skills in languages such as R, SQL, JavaScript, Java, CSS, and C++. Familiarity with statistical and data mining techniques like GLM/Regression, Random Forest, Boosting, Trees, text mining, and social network analysis is required. Experience with advanced machine learning algorithms and statistics, including regression, simulation, scenario analysis, modeling, clustering, decision trees, and neural networks, will be beneficial. In addition to technical skills, we are looking for candidates with 6-12 years of relevant experience in data modeling, ETL automation, AI/ML, and front-end design. You should have extensive experience in handling and classifying spend data using AI/ML techniques. Strong leadership, team management skills, proficiency in MS Excel and MS PowerPoint, high attention to detail, accuracy, and innovative problem-solving abilities are also desired. Preferred experience in supply chain management, particularly in applying AI/ML techniques to optimize operations, will be an advantage. Join us at Accenture, where we are committed to driving innovation and delivering exceptional solutions to our clients.,