16 Gradient Boosting 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.,

Who We Are Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Who You Are We are seeking a highly motivated Senior Data Scientist with strong technical expertise, business acumen, and strategic problem-solving abilities . In this role, you will independently own and build forecasting models. You will work closely with stakeholders across Product, Data Engineering & Analytics, and Business Strategy to identify opportunities to resolve business problems. This is a high-impact individual contributor role. What Youll Do Work in a dynamic and innovative company to develop cutting-edge solutions. Perform advanced data analytics to influence decision makers. Leverage data from diverse sources to provide insights and build new data driven tools. Partner with engineering teams to continuously improve our data quality. Develop machine learning based applications using supervised and unsupervised models using Python that optimize and personalize customer experiences or reduce manual effort on our internal teams through automated decision making. Develop and support models to enable things such as prescriptive insights, automated decisioning, and insights. Develop experiments to understand model impact, monitor live model analytics, and manage training and retraining pipelines. Work with stakeholders to intake complicated business problems and translate them into solvable data science projects. Partner with data engineering to take your model from development to deployed infrastructure. Brainstorm future use cases and contribute to the learning culture of the data science team. Partner with and mentor other data scientists and data analysts. Partner with multiple marketing teams, manage multiple projects and help conceptualize applications that directly drive company growth and strategy. You will connect machine learning applications to business needs and help facilitate process changes based on algorithmic solution implementation. What Youll Need You have Data Science experience building and validating machine learning and forecasting models in Python for a minimum of 5 years. You love performing advanced analytics to find insights and patterns. You have experience in supervised and unsupervised model techniques such as random forest, gradient boosting, support vector machines, k-means and hierarchical clustering, causal models, mixture models and experience in advanced modeling techniques such as reinforcement learning, neural networks, and natural language modeling. You have experience in delivering natural language projects utilizing techniques such as text summarization, topic modeling, entity extraction, semantic encoding, and valence analysis You have experience working in an agile business setting. You have experience with relational cloud databases like BigQuery and Snowflake and are comfortable working with unstructured datasets such as unstructured text. WHATS IN IT FOR YOU At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability. Show more Show less

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,

You will be working as a Machine Learning Intern for a duration of 6 months with a stipend of 20k per month. The internship involves a hybrid mode of working, with 3 days in the office and 2 days working from home. Your primary responsibilities will include designing and implementing cutting-edge machine learning models for complex tabular and time series data problems. Additionally, you will be tasked with developing innovative feature engineering techniques to maximize the value extracted from datasets. Researching and applying state-of-the-art algorithms in areas like automated machine learning (AutoML) and neural architecture search will also be part of your role. Furthermore, you will optimize models for performance and scalability in resource-constrained environments, contribute to the development of the company's core ML infrastructure and pipelines, and collaborate on end-to-end ML projects from problem definition to deployment and monitoring. Your involvement in strategic discussions to identify new opportunities for ML applications within the business and conducting independent research to stay updated on the latest ML advancements for tabular and time series data will be crucial. To excel in this role, you should possess a strong theoretical understanding of machine learning concepts, statistical modeling, and optimization techniques. Proven experience in developing and deploying ML models for tabular and time series data, along with advanced programming skills in Python and expertise in ML libraries and frameworks, is essential. Proficiency in working with large-scale datasets and distributed computing environments, as well as experience with modern ML techniques such as gradient boosting, neural networks, and ensemble methods, are also required. Preferred qualifications include contributions to open-source ML projects or research publications, as well as experience with cloud-native ML development and deployment. This internship offers a unique opportunity to work on cutting-edge AI and blockchain intersection projects, contributing to the company's growth and innovation in the field of machine learning.,

About Info Edge InfoEdge’s mission is to create world-class platforms that transform lives by continuously innovating. Our products and services are built keeping our customers in mind. We always delight our customers by delivering superior value through enhanced offerings on the internet and other platforms. Through our continuous investment across various businesses, especially in cutting-edge technology, machine learning and artificial intelligence (AI), we have built a robust system that constantly increases our predictive powers on customer behavior, and optimizes and improves our systems. Our various teams tirelessly work together to solve problems, innovate, and create something to empower our customers. At Info Edge, people are our core competitive advantage and we will continue doing all that is needed to attract and retain the best available talent. About BU: Corporate Function – Data Science Designation: AI Scientist Desired Experience: 0-3 Year Required Educational Qualification : PhD/ M.Tech / B.Tech with relevant experience from Tier 1 Campus As AI Scientist you will: Develop algorithms and build systems to extract seemingly unseen trends and information from user content such as resumes, job description and profile information available through various sources and in different modalities such as numeric, structure and unstructured texts and images. Identify potential new business problems that can be solved through machine learning. Ideate, formulate, create metrics and execute on such problems and get buy in from business. Identify potential data-driven machine learning solutions to improve user experience through personalization and prediction of user preferences. Build intelligent systems to capture and model the vast amount of behavior data to enrich the content understanding with behavioral information. Identify the appropriate and cutting edge machine learning tools for various supervised and unsupervised tasks in the NLP, deep learning, semantic search, LTR space for building highly accurate and scalable recommendation systems and information retrieval solutions. Design solutions for scalable and real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Participate in external forums /discussions, publish research papers, keep up-to-date on latest publications and build external/internal networks. Required Skills: Strong fundamental understanding and research experience in machine learning/Deep Learning/NLP/Information Retrieval/Artificial Intelligence areas. Strong applied knowledge of machine learning in solving real-world business problems with a significantly broad number of algorithms covering the landscape of classification, regression; discriminative, generative; supervised, unsupervised, semi-supervised; linear and non-linear dimensionality reduction, feature-extraction, feature selection, feature-learning. Industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. An excellent problem solving skills with a research oriented approach. Ability to capture, manage, create pipelines and process Big Data Desired Skills: Ability to understand Business challenges and define solutions aligned to the needs. Why Join us: This is a unique opportunity to work on innovative and disruptive technologies that are shaping the future of the industry. We are looking for candidates who are willing to work passionately in a fast- paced environment and are ready to enhance their skills by learning something new. Being a part of the InfoEdge team, you will be engaged in innovations, product development, integration with mobile and social media, technology, research and development, quality assurance, sales and marketing. To learn more about Info Edge visit http://www.infoedge.in/

As a Senior Data Scientist in the Global Data Science & Advanced Analytics team at Colgate-Palmolive, your role will involve leading projects within the Analytics Continuum. You will be responsible for conceptualizing and developing machine learning, predictive modeling, simulations, and optimization solutions to address business questions with clear dollar objectives. Your work will have a significant impact on revenue growth management, price elasticity, promotion analytics, and marketing mix modeling. Your responsibilities will include: - Conceptualizing and building predictive modeling solutions to address business use cases - Applying machine learning and AI algorithms to develop scalable solutions for business deployment - Developing end-to-end business solutions from data extraction to statistical modeling - Conducting model validations and continuous improvement of algorithms - Deploying models using Airflow and Docker on Google Cloud Platforms - Leading pricing, promotion, and marketing mix initiatives from scoping to delivery - Studying large datasets to discover trends and patterns - Presenting insights in a clear and interpretable manner to business teams - Developing visualizations using frameworks like Looker, PyDash, Flask, PlotLy, and streamlit - Collaborating closely with business partners across different geographies To qualify for this position, you should have: - A degree in Computer Science, Information Technology, Business Analytics, Data Science, Economics, or Statistics - 5+ years of experience in building statistical models and deriving insights - Proficiency in Python and SQL for coding and statistical modeling - Hands-on experience with statistical models such as linear regression, random forest, SVM, logistic regression, clustering, and Bayesian regression - Knowledge of GitHub, Airflow, and visualization frameworks - Understanding of Google Cloud and related services like Kubernetes and Cloud Build Preferred qualifications include experience with revenue growth management, pricing, marketing mix models, and third-party data. Knowledge of machine learning techniques and Google Cloud products will be advantageous for this role. Colgate-Palmolive is committed to fostering an inclusive environment where diversity is valued, and every individual is treated with respect. As an Equal Opportunity Employer, we encourage applications from candidates with diverse backgrounds and perspectives. If you require accommodation during the application process due to a disability, please complete the request form provided. Join us in building a brighter, healthier future for all.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

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.,

Genpact is a global professional services and solutions firm with over 125,000 employees in 30+ countries. Driven by curiosity, entrepreneurial agility, and the desire to create value for clients, we serve leading enterprises worldwide with deep business knowledge, digital operations services, and expertise in data, technology, and AI. Our purpose is the relentless pursuit of a world that works better for people. We are currently seeking a Business Analyst - Data Scientist to join our team. In this role, you will be responsible for developing and implementing NLP models and algorithms, extracting insights from textual data, and working collaboratively with cross-functional teams to deliver AI solutions. Responsibilities: Model Development: - Proficiency in various statistical, ML, and ensemble algorithms - Strong understanding of Time series algorithms and forecasting use cases - Ability to evaluate model strengths and weaknesses for different problems Data Analysis: - Extracting meaningful insights from structured data - Preprocessing data for ML/AI applications Collaboration: - Working closely with data scientists, engineers, and business stakeholders - Providing technical guidance and mentorship to team members Integration and Deployment: - Integrating ML 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 on NLP techniques and tools to stakeholders Qualifications: 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: - Experience in Predictive Analytics and Machine Learning techniques - Proficiency in Python/R/Any other open-source programming language - Knowledge of visualization tools such as Tableau, Power BI, Qlikview, etc. - Applied statistics skills - Experience with big data technologies (Hadoop, Spark) - Knowledge of cloud platforms (AWS, Azure, GCP) If you are passionate about leveraging your skills in data science and analytics to drive innovation and value creation, we encourage you to apply for this exciting opportunity at Genpact.,

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 Title: Senior Data Scientist Location: Bengaluru Experience: 8+ Years About Linarc: Linarc is revolutionizing the construction industry. As the emerging leader in construction technology, we are redefining how projects are planned, executed, and delivered. Built for general contractors, construction managers, and trade partners, Linarc is a next-generation platform that brings unmatched collaboration, automation, and real-time intelligence to construction projects. Our mission is to eliminate inefficiencies, streamline workflows, and drive profitabilityhelping teams deliver projects faster, smarter, and with greater control. Join us and be part of a high-impact, fast-growing team thats shaping the future of construction tech. If you thrive in a dynamic environment and want to make a real difference in the industry, Linarc is the place to be. This is a full-time position and you will be working out of our Bengaluru office. Roles and Responsibilities: Data Analysis & Modeling: Develop and implement machine learning models to solve business problems. Build predictive models and algorithms for customer behavior, product usage, and business outcomes. Conduct statistical analysis and hypothesis testing to uncover insights. Data Engineering & Processing: Clean, preprocess, and transform large-scale datasets from multiple sources. Develop and optimize data pipelines for real-time and batch processing. Business Insights & Reporting: Collaborate with business teams to define key performance indicators (KPIs). Develop dashboards and reports to communicate findings and performance. Present insights and recommendations to stakeholders and leadership. Product Improvement: Partner with product managers to integrate data-driven insights into product features. Monitor model performance and continuously improve accuracy and scalability. Run A/B tests to evaluate the impact of product changes. Research & Development: Stay updated with the latest developments in machine learning, AI, and data science. Explore and implement new data science techniques and tools to improve outcomes. Qualifications: Minimum 7+years of professional experience in Data Analytics/ Data Science/ AI/ Machine Learning. Deep analytical expertise in applying statistical solutions to business problems. Experience with exploratory data analysis with large data sets using SQL, Hive, Spark, or other tools. ML/DL tools, Scikit-learn, Tensorflow or PyTorch and proficiency in one or more statistical techniques: Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc. Experience working with visualization tools such as Tableau and Power BI. Demonstrated ability to innovate solutions and solve business problems. What will also help: Four or more years of experience in data science or machine learning in a product-focused environment. Four or more years of experience with one or more: C, Python, PyTorch, Java, JavaScript, NodeJs, ReactJs, VueJs. Four or more years of experience with relational or document databases. Adept at hypothesis testing and regression analysis. Experience in a SaaS product environment. Bachelors / Masters degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.

Job Description Job Title: Data Scientist Location: Bengaluru / Chennai Experience: 3+ Years About Linarc: Linarc is revolutionizing the construction industry. As the emerging leader in construction technology, we are redefining how projects are planned, executed, and delivered. Built for general contractors, construction managers, and trade partners, Linarc is a next-generation platform that brings unmatched collaboration, automation, and real-time intelligence to construction projects. Our mission is to eliminate inefficiencies, streamline workflows, and drive profitabilityhelping teams deliver projects faster, smarter, and with greater control. Join us and be part of a high-impact, fast-growing team thats shaping the future of construction tech. If you thrive in a dynamic environment and want to make a real difference in the industry, Linarc is the place to be. This is a full-time position and you will be working out of our Bengaluru office. Roles and Responsibilities: Data Analysis & Modeling: Develop and implement machine learning models to solve business problems. Build predictive models and algorithms for customer behavior, product usage, and business outcomes. Conduct statistical analysis and hypothesis testing to uncover insights. Data Engineering & Processing: Clean, preprocess, and transform large-scale datasets from multiple sources. Develop and optimize data pipelines for real-time and batch processing. Business Insights & Reporting: Collaborate with business teams to define key performance indicators (KPIs). Develop dashboards and reports to communicate findings and performance. Present insights and recommendations to stakeholders and leadership. Product Improvement: Partner with product managers to integrate data-driven insights into product features. Monitor model performance and continuously improve accuracy and scalability. Run A/B tests to evaluate the impact of product changes. Research & Development: Stay updated with the latest developments in machine learning, AI, and data science. Explore and implement new data science techniques and tools to improve outcomes. Qualifications: Minimum 3+years of professional experience in Data Analytics/ Data Science/ AI/ Machine Learning. Deep analytical expertise in applying statistical solutions to business problems. Experience with exploratory data analysis with large data sets using SQL, Hive, Spark, or other tools. ML/DL tools, Scikit-learn, Tensorflow or PyTorch and proficiency in one or more statistical techniques: Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor analysis, etc. Experience working with visualization tools such as Tableau and Power BI. Demonstrated ability to innovate solutions and solve business problems. What will also help: Four or more years of experience in data science or machine learning in a product-focused environment. Four or more years of experience with one or more: C, Python, PyTorch, Java, JavaScript, NodeJs, ReactJs, VueJs. Four or more years of experience with relational or document databases. Adept at hypothesis testing and regression analysis. Experience in a SaaS product environment. Bachelors / Masters degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.

In the IBM Chief Information Office,you wi be part of a dynamic team driving the future of AI and data science in arge-scae enterprise transformations. We offer a coaborative environment where your technica expertise wi be vaued, and your professiona deveopment wi be supported. Join us to work on chaenging projects, everage the atest technoogies, and make a tangibe impact on eading organisations. As a Data Scientist within IBM's Chief Information Office, you wi support AI-driven projects across the enterprise. You wi appy your technica skis in AI, machine earning, and data anaytics to assist in impementing data-driven soutions that aign with business goas. This roe invoves working with team members to transate data insights into actionabe recommendations. Key Responsibiities: Technica Execution and Leadership: Deveop and depoy AI modes and data anaytics soutions. Support the impementation and optimisation of AI-driven strategies per business stakehoder requirements. Hep refine data-driven methodoogies for transformation projects. Data Science and AI: Design and impement machine earning soutions and statistica modes, from probem formuation through depoyment, to anayse compex datasets and generate actionabe insights. Learn and utiise coud patforms to ensure the scaabiity of AI soutions. Leverage reusabe assets and appy IBM standards for data science and deveopment. Project Support: Lead and contribute to various stages of AI and data science projects, from data exporation to mode deveopment. Monitor project timeines and hep resove technica chaenges. Design and impement measurement frameworks to benchmark AI soutions, quantifying business impact through KPIs. Coaboration: Ensure aignment to stakehoders strategic direction and tactica needs. Work with data engineers, software deveopers, and other team members to integrate AI soutions into existing systems. Contribute technica expertise to cross-functiona teams. Required education Bacheor's Degree Preferred education Master's Degree Required technica and professiona expertise Bacheors or Masters in Computer Science, Data Science, Statistics, or a reated fied is required; an advanced degree is strongy preferred Experience: 5+ yearsof experience in data science, AI, or anaytics with a focus on impementing data-driven soutions Experience with data ceaning, data anaysis, A/B testing, and data visuaization Experience with AI technoogies through coursework or projects Technica Skis: Proficiency in SQL and Python for performing data anaysis and deveoping machine earning modes Knowedge of common machine earning agorithms and frameworksinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neura networks, and deep earning frameworks such as TensorFow and PyTorch Experience with coud-based patforms and data processing frameworks Understanding of arge anguage modes (LLMs) Famiiarity with IBMs watsonx product suite Famiiarity with object-oriented programming Anaytica Skis: Strong probem-soving abiities and eagerness to earn

Job Title: Data Scientist Location: Bangalore, India Experience: 3+ Years Role & Responsibilities: We are looking for a highly motivated Data Scientist to join our analytics team in Bangalore. This role is ideal for individuals who possess strong machine learning and data engineering skills and are eager to solve complex problems in the financial technology space. You will work on developing predictive models, building scalable data solutions, and contributing to key decision-making processes. Design, build, and validate machine learning models including Logistic Regression, Random Forests, GBM, and Survival Models. Perform rigorous model evaluation using techniques such as K-Fold Cross Validation, Out-of-Time (OOT) validation, and X-Tab analysis. Utilize Python (via PyCharm/Jupiter), scikit-learn, PyTorch or TensorFlow for end-to-end model development. Analyse large datasets using SQL and Excel to derive actionable insights. Develop and deploy APIs to serve machine learning models in production environments. Apply statistical techniques such as mean/variance analysis, probability distributions, and simulations to drive model accuracy and relevance. (Optional) Work with lending-specific metrics such as vintage curves, roll forward tracking, and bounce rates to enhance financial models. Strong ML skills: Logistic, Random Forest, GBM, survival model, K fold test, OOT, X-Tab etc. Experience using scikit-learn, pytorch or tensor flow. Experience: 3+ Years Python and usage of PyCharm/ Jupiter, SQL, Excel. Well versed in API development - Strong mathematical ability. mean, variance, probability distributions, simulation etc. Understanding of lending metrics such as vintage curve, roll forward, bounces etc. (Good to have not mandatory) Engineering background preferred IIT/NIT plus not must. Prior experience in Lending Fintech preferred.

Location:Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Must have skills:Data Scientist / Transformation Leader & at least 5 years in Telecom Analytics Good to have skills:GEN AI, Agentic AI, Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: Comms & Media (C&M) is one of the Industry Practices within Accentures S&C Global Network team. It focuses in serving clients across specific Industries Communications, Media & Entertainment. Communications Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the worlds leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualification Experience: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Educational Qualification: Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school

Job Description: We are seeking an experienced Data Scientist with expertise in advanced machine learning techniques to join our dynamic team. The ideal candidate will have hands-on experience developing and deploying models using ensemble methods and other cutting-edge ML algorithms, mostly in the US banking domain. Key Responsibilities: Develop and help deploy advanced machine learning models, including ensemble techniques, for customer lifecycle use cases (e.g., prescreen, acquisition, account management, collections, and fraud). Collaborate with cross-functional teams to define, develop, and improve predictive models that drive business decisions. Work with large datasets, utilizing tools like Python and SQL , to extract, clean, and transform data for modeling purposes. Ensure model robustness, interpretability, and scalability within banking environments. Strong problem-solving skills with the ability to handle complex datasets and turn them into actionable insights.