74 Decision Trees Jobs - Page 3

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.,

As a Data Scientist (AI & Machine Learning) at Infosys Finacle, located in Bangalore/Chennai, you will have the opportunity to be a part of transforming banking technology through the power of AI and data science. You will collaborate with top industry leaders to work on cutting-edge AI solutions, propose innovative ideas, and adapt in a fast-paced learning environment. Your responsibilities will include building AI algorithms, designing experiments to extract insights from large datasets, using predictive modeling to enhance customer experiences and achieve business goals, developing Explainable and Responsible AI models, conducting research to create prototypes, and identifying opportunities to apply data science insights across various teams and functions. We are looking for individuals with 2 to 10+ years of experience in data science or analytics, strong analytical and problem-solving skills, proficiency in statistical programming languages like Python and SQL, knowledge of advanced statistical techniques, experience with machine learning algorithms, and the ability to deploy models as APIs. Excellent communication and presentation skills are essential for conveying complex ideas to non-technical stakeholders. If you are ready to make an impact and contribute to the global digital banking transformation, please email your CV and details to sweta.singh09@infosys.com. The interview process consists of 3 rounds: Online Coding Assessment, Technical Round, and Hiring Manager Round. Joining Infosys Finacle means being a part of building core banking platforms for global financial institutions, learning and innovating with industry experts, and contributing to a global digital banking transformation. About Finacle: Finacle is a leading provider of digital banking solutions, partnering with financial institutions to drive better banking experiences. Our cloud-native solution suite and SaaS services enable banks to engage, innovate, operate, and transform effectively. As a business unit of EdgeVerve Systems, a product subsidiary of Infosys, we are committed to helping financial institutions of all sizes achieve digital transformation at speed and scale. For more information, please visit the Finacle website at https://www.edgeverve.com/finacle/solutions/. Please note that EdgeVerve Systems does not engage with external manpower agencies or charge any fees from candidates for recruitment. If you come across any such scams, please report them immediately.,

Navaera Worldwide is a global, full-service firm specializing in advanced knowledge management products and services tailored to assist Financial organizations in enhancing operational efficiency, managing risk, detecting fraud, and gaining a competitive advantage. The company, a privately held entity, boasts a diverse client base across the globe, including major corporations within the financial services industry. Navaera Worldwide, under the brand Navaera Global Services, offers sophisticated business products and solutions to organizations of varying sizes. With offices situated across three continents, Navaera Worldwide's global headquarters is based in New York, with additional locations in Toronto, Canada, and Baroda, India. As a Specialist in Emerging Systems Engineering, you will be expected to possess a solid 3 to 5 years of experience range and be adept at working in areas such as Data Analytics, Computer vision, NLP, and OCR-related tasks. Your responsibilities will include data collection, dataset preparation, architecture modeling, model training/testing, and deployment. Additionally, you should have experience in managing digital data extraction and processing, creating training and testing pipelines with diverse data aspects, and developing model architectures from scratch or modifying pre-trained models. The ideal candidate must stay updated with the latest AI trends to ensure operational processes remain current. You will be required to identify opportunities for process enhancements, propose system modifications, and work with minimal technical supervision while efficiently managing multiple program priorities. Collaboration within a team environment is crucial, as you will be tasked with driving cross-team solutions that may have complex dependencies and requirements. Your qualifications should include a B.E./B.Tech in Computer Science/Statistics/IT/ECE stream, with an M.S. or Ph.D. in Applied Mathematics, Statistics, Computer Science, Operations Research, Economics, or equivalent. You should have 3-5 years of hands-on experience in data science, machine learning, and deep learning, along with proficiency in C/C++/Java/Python for developing machine learning and deep learning solutions. Experience in building and deploying Machine Learning solutions using various supervised and unsupervised ML algorithms is essential. Moreover, you should have at least 3-5 years of practical experience with Python and frameworks such as TensorFlow, PyTorch, or MXnet. A good command of ML libraries like scikit-learn, NumPy, pandas, and Keras, as well as natural language processing using NLTK, spaCy, and Gensim, is required. Strong communication and interpersonal skills, familiarity with decision science tools and techniques, excellent problem-solving abilities, and the capacity to work efficiently in a fast-paced, deadline-driven environment are all highly valued in this role. Demonstrating a strong work ethic, a sense of collaboration, and ownership is imperative for success within the organization.,

Amplework Software is a full-stack development agency that specializes in providing end-to-end software development solutions to clients globally. The company is dedicated to delivering high-quality products that meet business requirements by utilizing advanced technologies. Their expertise includes custom software development, mobile applications, AI-driven solutions, and enterprise applications. By joining Amplework Software, you will become part of an innovative team that is focused on driving digital transformation through technology. As an Mid-Level Python and AI Engineer at Amplework Software, your responsibilities will include assisting in building and training machine learning models using frameworks like TensorFlow, PyTorch, and Scikit-Learn. You will have the opportunity to experiment with pre-trained AI models for NLP, Computer Vision, and Predictive Analytics. Additionally, you will work with both structured and unstructured data, conduct preprocessing, and engage in feature engineering. Collaboration with data scientists and software engineers to integrate AI solutions into real-world applications is a key aspect of this role. Continuously learning, experimenting, and optimizing models to enhance performance and efficiency is also part of the job. Ideal candidates for this position should possess a strong foundation in Python, basic machine learning concepts, and a willingness to learn. Required qualifications include a Bachelor's degree in Computer Science, Engineering, AI, or a related field, proficiency in Python with experience in writing optimized and clean code, strong problem-solving skills, and an understanding of machine learning concepts such as linear regression, classification, decision trees, and feature engineering. Experience with data processing libraries like Pandas, NumPy, and Matplotlib, as well as basic knowledge of AI models and neural networks using frameworks such as Scikit-Learn, TensorFlow, or PyTorch are also required. Preferred qualifications for this role include experience with Natural Language Processing (NLP) using transformers, BERT, GPT, or OpenAI APIs, basic understanding of AI model deployment using Flask, FastAPI, or TensorFlow Serving, experience with SQL or NoSQL databases for querying datasets in AI applications, and participation in AI-related competitions, hackathons, or open-source projects. In addition to technical skills, soft skills and work ethics are also important for this role. Candidates should have a strong analytical and problem-solving mindset, the ability to work collaboratively in a team, communicate technical concepts effectively, eagerness to learn and apply new AI techniques, and excellent English communication skills, both written and verbal. Candidates who prefer strictly rule-based programming without flexibility for AI experimentation may not be suitable for this position due to the requirement for strong problem-solving skills and quick learning abilities. A face-to-face interview will be conducted, and applicants should only apply if they are able to attend the interview at the office. Joining the Amplework Software team offers the opportunity to be part of a passionate and collaborative team, work on cutting-edge projects, make a real impact, enjoy competitive benefits, and experience a great working environment.,

The Associate Manager, Compliance Analytics supports the development and implementation of compliance analytics across the global compliance organization. You will be responsible for designing and developing analytical solutions, generating insights, and fostering a culture of ethics and integrity. Your role will involve transforming data from multiple systems, designing the analytics approach, and executing the analytics. Your responsibilities will include designing, developing, and maintaining analytics to provide business insights, enabling risk-intelligent decisions, informing compliance risk assessment processes, and supporting remediation activities. You will be involved in scoping, gathering requirements, developing analytics models, validating and testing models, and communicating results to stakeholders for analytics projects. Additionally, you will support the execution of analytics initiatives to enhance the Global Compliance program and provide actionable insights through data and analysis to achieve business objectives. Furthermore, you will contribute to the development of standardized analytics processes and frameworks, including documentation and validation of work. You will also be responsible for setting up sustainable analytics solutions, including data pipelines and automated refresh schedules as necessary. Collaboration with compliance officers, IT, and stakeholders to understand business objectives and provide reliable and accurate reports, insights, and analysis to inform decision-making is an essential aspect of this role. As part of your duties, you will lead a culture of continuous improvement by enhancing existing databases, data collection methods, statistical methods, technology, procedures, and training. You will partner with data custodians and process experts to ensure the quality of data and definitions to support the building of reliable data models and analysis. Additionally, coaching and developing junior team members will be a key component of this role. To qualify for this position, you should have 8+ years of relevant work experience in Python, Advanced SQL, R, Azure, Databricks, PySpark, and PowerBI. A strong knowledge and experience in advanced analytics tools and languages to analyze large data sets from multiple sources are required. A BTech in Computer Science, IT, MSc in Mathematics/Statistics, or equivalent courses from an accredited university is necessary. You should possess a strong understanding of algorithms, mathematical models, statistical techniques, data mining, and experience implementing statistical and machine learning models. Experience with analyzing accounting and other financial data, as well as demonstrating excellent ability to exercise discretion and maintain confidentiality, are essential. Knowledge and experience with data transformation and cleansing, data modeling, and database concepts are also preferred.,

Key Responsibilities: 1. Technical Execution and Leadership: Develop and deploy AI models and data analytics solutions. Support the implementation and optimization of AI-driven strategies per business stakeholder requirements. Help refine data-driven methodologies for transformation projects 2. Data Science and AI: Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights. Learn and utilize cloud platforms to ensure the scalability of AI solutions. Leverage reusable assets and apply IBM standards for data science and development. 3. Project Support: Lead and contribute to various stages of AI and data science projects, from data exploration to model development. Monitor project timelines and help resolve technical challenges. Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs. 4. Collaboration: Ensure alignment to stakeholders strategic direction and tactical needs. Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems. Contribute technical expertise to cross-functional teams.

As part of the Data Science team in Colruyt, youwill have an opportunity to work with culturally diversified group ofindividuals, ensure business take strategic decisions by providing right datainsights. We are looking for an individual with Passion, Innovation, out of the box thinking to join our team . Build a portfolio of data opportunities for specific business partners based on your knowledge of the data and the business. Support business partners in translating their needs into specific research questions that can be addressed in a data science project. Apply techniques of data preparation, quality control, completeness, distribution, consistency, outliers, data, or variable transformation. Apply mathematical , statistical , and modeling techniques in a suitable environment. Use statistical analysis to support strategic decision-making . Support partners in the correct interpretation and application of analysis results. Training Business partners interpret analysis results independently or translating analysis results into the right actions. Collaborate closely with Data Science Engineers to support the entire data pipeline process. Evaluate the long-term validity of the analytical solution. Follow up on developments in the field of statistical analysis, mathematical modeling, optimization, and integrate these into practice. Requirements Should have 12+ years of working experience in Data-related projects. At least 7+ years of relevant experience as a Data Scientist. In-depth knowledge of statistical methods for data analysis, interpretation , and application of these techniques to solve a business problem. Experience in applying a variety of analytical algorithms , including but not limited to linear and logistic regression, Bayesian analysis, decision trees, random forest, boosting techniques, forecasting, time series, clustering, neural networks, and others. Proficiency in Python is expected to perform Data Science activities. Strong analytical and problem-solving skills . Ability to work in a team-oriented, collaborative environment . Excellent communication and interpersonal skills Experiencein text mining, NLP, understanding of image processing. Bachelors or masters degree in a relevant field such as Statistics, AI / ML / NLP is an added value.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Business Analyst Data Scientist In this role, the person is responsible for developing and implementing NLP models and algorithms, extracting insights from textual data, and collaborating with cross-functional teams to deliver AI solutions. Responsibilities Model Development: Familiar with different statistical, ML and ensemble algorithms Proficient with Time series algorithms and forecasting usecases Understand model specific strengths and weaknesses and know-how of suitable and unsuitable models for different problems Understand evaluation metrics and recommend the correct evaluation metric for a problem type Data Analysis: Extract meaningful insights from structured data. Preprocess data for ML / AI applications Collaboration: Work closely with data scientists, engineers, and business stakeholders. Provide technical guidance and mentorship to team members. Integration and Deployment: Integrate ML models into production systems. Implement CI/CD pipelines for continuous integration and deployment. Documentation and Training: Document processes, models, and results. Provide 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. Strong programming skills in Python and R Experience with DS frameworks (SKLEARN, NUMPY). Knowledge of machine learning concepts and frameworks (TensorFlow, PyTorch). Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Preferred Qualifications/ Skills Predictive Analytics Experience inMachine Learning techniques Experience in Python/R/ Any other open-source programming language Building and implementing models, using/creating algorithms and creating/running simulations using a variety of Tools Good to have - Experience in visualization tools such as Tableau, Power BI, Qlikview etc. Good applied statistics skills, such as distributions, statistical testing, regression, etc. Knowledge and experience of tools/techniques: Forecasting, Linear Regression, Logistic Regression, Regularization, Segmentation (Decision Trees, CHAID, CART), Cluster Analysis, Factor Analysis, variable screening, Machine Learning Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning etc. Experience with big data technologies (Hadoop, Spark). Knowledge of cloud platforms (AWS, Azure, GCP). Job Business Analyst Primary Location India-Hyderabad Education Level Bachelor's / Graduation / Equivalent Job Posting Apr 1, 2025, 8:47:23 AM Unposting Date May 1, 2025, 7:29:00 PM Master Skills List Digital Job Category Full Time,

Job Role: Lead Data Scientist. Location: Bengaluru, Karnataka. Mode : Work from Office Notice Period: Immediate to 20 days. Job Description The incumbent will be part of the Predictive Analytics, Digital Analytics, Data Sciences, Advanced Visualization, Insights & Experimentation team and will report to the Manager/Senior Manager. He/she will be an individual contributor working on multiple data sciences, advanced visualization and data management initiatives across multiple companies and industries leveraging traditional and big data. The incumbent will have the unique opportunity to witness the application of analytics across multiple industry verticals. Close partnership with business and the senior leadership of multiple Tata Companies will enable a clear understanding of the business perspectives and the application of analytics for solving real business problems. Key Responsibilities: • Apply AI| ML , Deep Learning, Computer Vision, Data Mining/ Data Analysis methods using a variety of data tools, building and implementing models using algorithms and creating/ running simulations to drive optimisation and improvement across business functions • Assess accuracy of new data sources and data gathering techniques • Perform Exploratory Data Analysis, detailed analysis of business problems and technical environments in designing the solution • Apply Supervised, Unsupervised, Reinforcement Learning and Deep Learning algorithms • Apply advanced Machine Learning Algorithms and Statistics: o Regression, Simulation, Scenario Analysis o Time Series Modelling o Classification - Logistic Regression, Decision Trees, SVM, KNN, Naive Bayes o Clustering, K-Means, Apriopri o Ensemble Models - Random Forest, Boosting, Bagging o Neural Networks • Lead and manage Proof of Concepts and demonstrate the outcomes quickly • Document use cases, solutions and recommendations • Work analytically in a problem-solving environment • Work in a fast-paced agile development environment • Coordinate with different functional teams to implement models and monitor outcomes • Work with stakeholders throughout the organization to identify opportunities for leveraging organisation data and apply Predictive Modelling techniques to gain insights across business functions - Operations, Products, Sales, Marketing, HR and Finance teams • Help program and project managers in the design, planning and governance of implementing Data Science solutions Experience and Skills: • 8+ years of professional working experience in Analytics • Experience in Leading Team and Guiding through Project End to End Delivery. - Experience in Retail, Financial Services and Manufacturing • Experience using statistical packages of R, Python and Spark ML to work with data and draw insights from large data sets • Experience with distributed data/ computing tools: Hadoop, Hive, Spark, Python • Experience with SQL • Experience visualizing/ presenting data for stakeholders using matplot, ggplot or Excel or Tableau • Excellent written and verbal communication skills for coordinating across teams Education qualification: • Bachelors/ Masters in a quantitative discipline (Statistics, Econometrics, Mathematics, Engineering and Science)

AI/ML Engineer to join our fast-growing. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and AI-driven applications that deliver business value and customer impact. Key Responsibilities Research and develop machine learning models using supervised, unsupervised, or reinforcement learning techniques. Deploy models into production using MLOps best practices (e.g., containerization, CI/CD, model monitoring). Work on datasets involving structured and unstructured data (e.g., text, image, video, time-series). Collaborate with data engineers, product managers, and other stakeholders to define problem statements and deliver solutions. Continuously improve model performance and scalability using experimentation and model evaluation techniques. Stay updated with the latest trends and breakthroughs in AI/ML (e.g., LLMs, transformers, generative AI). Required Qualifications Bachelors/Masters/Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field. Strong coding skills in Python (must), with knowledge of libraries like scikit-learn, PyTorch, TensorFlow, Hugging Face, OpenCV , etc. Experience building and tuning ML models from scratch. Solid understanding of ML lifecycle, from data preprocessing to model deployment. Hands-on with SQL , data manipulation tools ( Pandas , NumPy ), and visualization tools ( Matplotlib , Seaborn , Plotly ). Experience with cloud platforms (AWS/GCP/Azure) and tools like Docker, Kubernetes, MLflow is a plus. Preferred Skills Exposure to NLP , LLMs , chatbots , speech processing , or computer vision applications. Experience with GenAI models like GPT, DALL•E, or stable diffusion. Knowledge of prompt engineering, vector databases (like FAISS, Pinecone ), or LangChain is a bonus. Publications or participation in AI/ML competitions (e.g., Kaggle, NeurIPS, CVPR) is a strong plus.

Overview Provide advanced analytics support for the LATAM Sector in the Insights Services Center; a part of the broader Global Business Services function in Hyderabad, India. This role will help to enable accelerated growth for PepsiCo by developing custom descriptive analytics approaches for LATAM to drive deeper understanding of business performance drivers both at the National / Regional / State /City level. Primary responsibilities include developing/enhancing statistical models to address key business questions associated with Growth Driver Modeling, Pricing, Assortment, Market Structure, Innovation Forecasting, and Category Growth Forecasts, Portfolio growth model, Ambition related assignments for the key markets of LATAM. Additionally, this role will also support the consumer insight team by collating learnings from a variety of sources, to help inform the development of future insights strategies for various brands with in Bevareages / Snacks . The role will have short-term responsibilities for knowledge transfer from the Vendors and effectively establishing business process and communication methods with teams they support; both are crucial requirements to enabling the organization to deliver answers to on-going business questions Responsibilities Functional Responsibilities: Support delivery of descriptive and predictive analytics as defined by the SLA (Service Level Agreement) within the LATAM Business Service Service Center Execute deep descriptive analytics of business performance and drivers to supplement standard reporting and inform data-driven decisions Identify, assess, and visualize key market share drivers for LATAM Categories, as a growth catalyst to prioritize and enable brand planning across portfolio Support LATAM regions annual SKU optimization process for the portfolio; analyzing impact by channel, customers and region as needed based on HQ delivered recommendations & targets Advise and share Advanced Analytics models and best practices with Regional Category Managers to leverage and build Advanced Analytics capability. Develop, maintain, and apply statistical models to business questions - including forecasting, price sensitivities/corridors, drivers analysis, market structure, etc. Forecast market growth leveraging (PGM an internal tool) on an annual basis to inform PEPs long-term expectations for growth Collate and format consumer learnings from custom insight outputs, sales performace reporting, industry periodicals, and social listening resources, etc to help inform and develop future consumer insights strategies Provide responses to ad-hoc follow-ups when double-click (additional questions) required with tables/charts for relevant data Support relationships with the key end-user stakeholders in LATAM and region offices Own flawless execution of analytics exercises Responsible for managing multiple priorities; being able to manage deadlines and deliverables Lead communication with Business Partners and potentially end-users on matters such as available capacity, changes of scope of existing projects and planning of future projects Deliver outputs in line with the agreed timelines and formats Flag and monitor any business risks related to delivering the requested outputs Partner with stakeholders and service center leadership to develop and finetune internal COE processes (work-flow mapping, pain-points and bottlenecks management) both related to service delivery and internal center operations Improve existing processes based on frequent Business Partner & end-user feedback loop People and Project Management Responsibilities Develop new skillsets among team members related to advanced analytics by conducting training and period review Promotes cross functional seamless communication, sharing know how and creating same quality of experience across sector markets Qualifications 6+ years of experience in the field of analytics Ability to convert insights into story that answers critical business questions. Hands on in coding in tools like R and Python ( both or at least Hands on in MS excel(advanced) and SQL Understanding of data structures, adept in data cleaning, structure, and aggregation as per need End-to-end project management. Expert of statistical techniques like regression, forecasting, decision trees and modelling process- concept and coding. Ability to design model architecture and translate business problem into analytical problem Ability to visualize data set and identify KPIs that will help decision making. Good PowerPoint skills. Experience in ML techniques, cloud compatible tech stacks, understanding of data pipeline creation preferable

Job description Job description Job Summary: We are looking for a results-driven and innovative Data Scientist with 46 years of experience in data analysis, machine learning, and product optimization. The ideal candidate will have a strong foundation in Python, SQL, and cloud services, along with practical exposure to GenAI, LLMs, and MLOps frameworks. You will be responsible for building scalable data pipelines, developing machine learning models, and solving real-world business problems with data-driven solutions. Key Responsibilities: Design and deploy LLM-powered solutions (e.g., RAG, LangChain, Vector DB) to enhance business processes. Build and fine-tune traditional ML models (Random Forest, Decision Trees) for predictive analytics. Optimize LLM performance using LoRA fine-tuning and post-training quantization. Develop and deploy containerized AI applications using Docker and FastAPI. Collaborate with agents like CrewAI and LangSmith to automate document processing and data extraction workflows. Implement Python & SQL-based ETL pipelines for real-time data ingestion. Design dashboards and KPI monitoring tools using Metabase to enable data-driven decision-making. Create data consumption triggers and automate reporting for international stakeholders. Moderate large-scale live virtual data science classes and provide operational support. Required Skills: Programming: Python, SQL, FastAPI ML & AI: Random Forest, Decision Trees, Clustering, PCA, DL, NLP, Transformers, Gen AI Frameworks/Tools: LangChain, MLflow, Kubeflow, CrewAI, LangSmith DevOps: Docker, Git Databases: MySQL, PostgreSQL, MongoDB Cloud: AWS (S3, EC2) Visualization: Metabase Other: Experience with LLM fine-tuning and quantization Role & responsibilitiesRole & responsibilities Preferred candidate profile

GM Analytics Solutions is looking for a driven, dedicated and experienced Data Scientist Essential Responsibilities: As a Data Scientist, you will solve complex challenges and identify new opportunities using a combination of Data analytical expertise, business acumen, strategic thinking, and project & relationship management skills. He/she will work with the Product Owner, VP of IT capture business requirements, The Data Scientist will partner with the development team (on-site and off-shore) to execute the projects. Must have strong knowledge about statistical techniques like segmentation, predictive modeling, statistical modeling clustering, linear regression, logistic regression, SVM, Random Forest, Gradient Boosting, Optimization and time series forecasting to derive meaningful insights from data and to build high level solutions that predict and optimize business outcomes based on client's success criterion. Requirement: Minimum with 3 years hands-on in machine learning algorithms Should be familiar with Supervised and Unsupervised algorithms and should have worked on Anomaly detection. Excellent understanding of machine learning techniques and algorithms and should be proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain, Monte Carlo, Gibbs Sampling, Evolutionary Algorithms, Support Vector Machines, Neural Networks, k-NN, Naive Bayes, SVM, Decision Forests etc Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial and multinomial regression, ANOVA); Classification techniques, Clustering, Principal Component Analysis, factor analysis; Decision Tree techniques (e.g., CART, CHAID) Should have some experience working with time series data Comfortable working with the Engineering Team to design, code, train, test, deploy and iterate on enterprise-scale machine learning systems Expert in Data processing, wrangling and visualization Experience with automated feature engineering and dealing with large datasets Should have experience in deploying machine learning model Very Good analytical thinking with problem-solving abilities Should have experience in deploying machine learning model Good knowledge on writing complex SQL queries for selecting data from database. Comfortable working with Python, Jupyter Notebook and ability to work with machine learning frameworks. Deliver results within committed scope, timeline, and budget Role & Responsibility: Works to design and develop analytical/ data mining/ machine learning/deep learning models as part of data science solutions Perform quantitative and qualitative analysis like (raw) data analysis, statistical modelling, data deep-dives etc. to acquire insights from data Data pulling or creating from different sources Responsible for analyzing data from multiple data sources (DBs, flat files, etc.), and building predictive models using Python Work to design and build an end-to-end prototype data science solution to a business problem in any specific sector/ function, more specific to healthcare domain. Develop actionable insights to drive outcome. Translate insights into an analysis report and communicates the insights back to the requestor.. Different models and their performances in Real time and Batch developed using Python (Pandas)/MLib/PySpark and opting the better solution depending on the cases Validate the models - statistically as well as from business perspective in discussions with business stakeholders Work to support and guide model deployment and model lifecycle management Map insights to action items (working with stakeholders) in order to improve business metrics Facilitate monitoring of actions to drive outcome: Monitor actions (targeted business outcomes achieved)- by providing guidance and feedback to the operations team Project governance: Ensure compliance to governance model. Seek and manage customer feedback in order to ensure strong customer satisfaction on projects Competency Requirements: Must possess the following knowledge, skills, and abilities to perform this job successfully: Familiar with standard concepts, practices, and procedures within the field. Creativity and latitude required. Ability to work in a fast-paced, result-driven, and complex healthcare setting. Ability to meet strict deadlines. Excellent analytical, problem-solving, organization and time management skills. Takes a sense of ownership Capable of embracing unexpected change in direction or priority. Excellent communication skills. Strong self-sufficiency and initiative working on database projects. This position may be modified to reasonably accommodate an incumbent with a disability. This job requires the ability to work with others in a team environment, the ability to accept direction from superiors and the ability to follow Company policies and procedures. Regular, predictable and dependable attendance is essential to the satisfactory performance of this job. GM Analytics is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.to join our Gurgaon based team of IT professionals. The position is responsible for projects heavy in back-end database work including creating and maintaining interfaces between multiple sources and the database.

Exp - 6- 10 Years Level - Senior Consultant Skill - ML OPS with Gen AI Location - Bengaluru Event on 9th May in Bangalore location Hybrid Mode (2 days WFO in a week) Education - B.Tech/B.E/MS/MBA ML OPs Engineer Required: 6-10 years of Consulting, Data, and Analytics experience Experience in descriptive & predictive analytics, both theoretical and practical knowledge in basic ML algorithms like linear and non-linear regression, linear and non-linear classification, dimensional reduction, anomaly detection, statistical concepts and techniques like theoretical distributions, parametric and non-parametric inference 6+ years of experience implementing & executing data science projects throughout the entire lifecycle: Developing/designing and implementing solutions E2E in production. Strong knowledge of Python or R Programming experience with Node.js, SQL, Java, JavaScript OR PERL Experience in cloud-based data platforms on AWS, GCP and Azure Understanding of multi-tier application architectures Ability to develop, test and maintain programming environments and architectural standards Foundational understanding of application development lifecycle and using tools like ANT, Maven, Gradle and Version control (SVN OR GIT OR BitBucket) Experience with working in an agile development lifecycle and continuous integration processes using tools such as Jenkins Experience in doing deployments for Java, .NET , Angular , Node.js , PHP, Python applications using Jenkins/Bamboo Experience on code quality assessment tools and integration with CI tool Strong logical structuring and problem-solving skills Strong verbal, written and presentation skills Preferred Additional Experience in using Spark either with Scala or Python Experience with different database types like RDS and NoSQL Experience in cloud deployments Knowledge of working in a Linux environment Strong understanding and experience configuring, managing and supporting applications using tools such as OpsWorks, Datadog and CloudWatch on AWS Experience in Docker /Swarm / Kubernetes Experience or exposure to Test Driven Development Experience (Junit / TestNG) Experience on Behavior Driven Development Experience (Cucumber / Selenium) Expertise in any commercial data visualization tool such as Tableau, Qlik, Power BI Experience with real time data movement solutions that use security and encryption protocols while data is in transit