648 Xgboost Jobs - Page 14

Verint is a leader in CX automation. The world’s most iconic brands rely on our open platform and team of AI-powered bots to create tangible AI business outcomes, now. Today’s organizations face skyrocketing expectations for delivering better customer experiences (CX) across every channel. But hiring more workers and increasing workforce expenses isn’t a sustainable option. AI offers a solution – and that’s where Verint comes in. We empower brands with groundbreaking AI via our next-gen open platform. The first of its kind, Verint Open Platform helps organizations increase CX automation to achieve their strategic objectives and realize significant ROI. The Verint Open Platform provides a team of AI-powered bots to augment human staff across the enterprise, including contact centers, web/mobile channels, branches, back offices, CX offices, and more. The result? Organizations can create capacity, lower costs, and continually improve CX. It’s all possible with CX automation. Center of Excellence in Financial Analytics and Innovation Team Description: The Center of Excellence in Financial Analytics comprises a dynamic and diverse team of professionals with expertise in finance, computer science, data analytics, data engineering, machine learning & AI, and FP&A. Our team is dedicated to driving innovation, leveraging analytics techniques, and utilizing financial insights to optimize decision-making within the organization. Collaborative and driven, our team members work closely together to deliver high-quality business insights and contribute to the success of the CFO Organization. Location: Bangalore India Job Title: Specialist – Machine Learning and AI Job Summary: We are seeking a highly skilled and motivated Specialist – Machine Learning and AI to join our Financial Analytics Center of Excellence in Bangalore. This role will support cross-functional business teams—including CFO, CTO/Product Analytics, Investor Relations, Corporate FP&A, Customer Success, Sales Operations, Reporting & Consolidation, and Partner Alliances—by designing and deploying advanced AI/ML solutions to solve complex business challenges. The ideal candidate will bring 5–10 years of hands-on experience in applying machine learning and artificial intelligence in financial analytics, product usage analysis, and general business operations in a B2B software/SaaS environment. Job Description: Collaborate with finance, product, and operations stakeholders to understand business questions and deliver ML/AI-driven solutions that improve forecasting, anomaly detection, and process automation. Lead the design and deployment of machine learning models including supervised, unsupervised, and reinforcement learning approaches to solve use cases in revenue forecasting, GL mapping, customer expansion recommendations, customer retention, churn and product analytics. Own the end-to-end ML pipeline: data preparation, feature engineering, model selection, training, validation, and deployment. Design and implement MLOps and automation pipelines to streamline the deployment and monitoring of ML models. Enhance and maintain existing models for intelligent classification to support business growth. Partner with data engineers and analysts to ensure data quality, scalable architecture, and secure model integration with business applications and dashboards. Provide thought leadership in identifying emerging AI/ML trends and proactively propose innovative use cases to improve business outcomes. Generate explainable, transparent outputs that can be translated into business actions and executive-level insights. Required Qualifications: Bachelor's or master’s degree in computer science, Data Science, Applied Mathematics, Statistics, or a related field. 5–10 years of hands-on experience applying machine learning and AI in a business context, preferably in the software/SaaS industry. Strong programming skills in Python and libraries like scikit-learn, XGBoost, TensorFlow, PyTorch, etc. Demonstrated success with ML use cases such as: GL classification, predictive modeling for financial KPIs, customer behavior prediction, or recommendation systems. Experience working in cross-functional teams with finance, sales, customer success, and product functions. Proficiency in SQL and working with structured/unstructured datasets. Ability to communicate complex technical solutions clearly to non-technical stakeholders and executive audiences. Preferred Qualifications: Prior experience supporting FP&A, Product Analytics, or GTM Strategy functions. Exposure to cloud-based ML deployment (Azure, AWS, or GCP). Basic knowledge of Large Language Models (LLMs) and Generative AI tools. Familiarity with BI tools such as Power BI or Tableau for integrating ML output into business reporting. Why Join Us? Be part of a growing, high-impact Financial Analytics Center of Excellence. Work on meaningful business challenges using cutting-edge AI/ML approaches. Collaborate with senior business leaders across Business Finance, Product, and Customer organizations. Drive innovation and help shape the next phase of our AI/ML capability in a dynamic business team in global software company.

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. AI/ML & Credit Risk Analytics Professional – Job Specification Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Years of Experience: Candidates with 8+ years of hands on experience Position: Manager Industry: Telecom / Network Analytics / Customer Analytics Required Skills: Successful candidates will have demonstrated the following skills and characteristics: Must Have Experience working in the telecom industry across domains such as customer churn prediction, ARPU modeling, pricing optimization, and network performance analytics Strong understanding of telecom KPIs and datasets, such as CDRs, service usage data, network QoS, and customer lifecycle metrics Proficiency in machine learning techniques, including classification, regression, clustering, and time-series forecasting Strong command of statistical techniques (e.g., logistic regression, hypothesis testing, segmentation models) Hands-on experience in Python, SQL, and PySpark for large-scale data handling and modeling Experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch Knowledge of data wrangling, feature engineering, and preparing telecom datasets for modeling Proficiency in data visualization tools such as Power BI, Tableau, or Looker Nice To Have Exposure to cloud platforms (Azure ML, AWS SageMaker, GCP Vertex AI) Experience working with telecom OSS/BSS systems or customer segmentation tools Familiarity with network performance analytics, anomaly detection, or real-time data processing Strong client communication and presentation skills Roles And Responsibilities Lead and manage analytics projects within the telecom domain, driving design, development, and delivery of data science solutions Work closely with US-based clients and consultants to understand telecom-specific use cases and define analytical approaches Guide teams in building and validating predictive models that address key business needs like churn, upsell, ARPU, and service quality Translate business problems into data-driven solutions, and ensure alignment with KPIs and expected outcomes Review and manage data quality, model robustness, and explainability for telecom-specific deployments Present insights and analytical recommendations to internal stakeholders and client leadership teams Mentor and upskill junior team members while fostering a culture of collaboration and continuous learning Support practice development activities including IP creation, proposal support, and client engagement planning Professional And Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Master’s Degree /MBA from reputed institute

***Local Gujarat or Ahmedabad candidates only *** Strong expertise in Python Hands-on experience with machine learning models like Random Forest, XGBoost, etc. Preferred: Exposure to large language models (LLMs) and natural language processing (NLP) techniques Solid foundation in statistical analysis and machine learning methodologies Proficient in data cleaning, preprocessing, and feature engineering Comfortable working with data visualization tools and techniques Job Types: Full-time, Permanent Pay: From ₹25,000.00 per month Benefits: Health insurance Location Type: In-person Schedule: Evening shift Work Location: In person

***Local Gujarat or Ahmedabad candidates only *** Strong expertise in Python Hands-on experience with machine learning models like Random Forest, XGBoost, etc. Preferred: Exposure to large language models (LLMs) and natural language processing (NLP) techniques Solid foundation in statistical analysis and machine learning methodologies Proficient in data cleaning, preprocessing, and feature engineering Comfortable working with data visualization tools and techniques Job Types: Full-time, Permanent Pay: From ₹25,000.00 per month Benefits: Health insurance Location Type: In-person Schedule: Evening shift Work Location: In person

What will your role look like Design, train, evaluate, and deploy traditional ML models as well as Generative AI-based applications. Work on supervised, unsupervised, and deep learning models including regression, classification, clustering, and sequence models. Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, hyperparameter tuning, and evaluation. Develop and optimize LLM-based workflows using LangChain, LangGraph, and orchestration frameworks. Fine-tune, evaluate, and integrate LLMs such as GPT, LLaMA, Claude, Mistral, Falcon, Cohere, and Gemini. Implement Retrieval-Augmented Generation (RAG) using embeddings and vector stores like FAISS, Pinecone, or Chroma. Apply prompt engineering, LoRA, PEFT, and adapter-based fine-tuning to optimize LLMs for specific tasks. Build Agentic AI systems with tool-use capabilities and reasoning chains (e.g., ReAct, AutoGPT, BabyAGI, CrewAI). Use Hugging Face for leveraging pre-trained models and datasets for rapid experimentation. Collaborate with product, data, and engineering teams to productionize AI solutions using scalable cloud infrastructure. Why you will love this role Besides a competitive package, an open workspace full of smart and pragmatic team members, with ever-growing opportunities for professional and personal growth Be a part of a learning culture where teamwork and collaboration are encouraged, diversity is valued and excellence, compassion, openness and ownership is rewarded. We would like you to bring along Strong grasp of core ML concepts such as model selection, evaluation metrics, bias/variance tradeoff, overfitting/underfitting, etc. Good exposure on using Azure Open AI and hosting applications in Azure environment Experience in building and tuning models using scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Experience in building ML pipelines with feature engineering, model tuning, cross-validation, and A/B testing. Proficiency in LangChain, LangGraph, and integrating with Hugging Face Transformers Ecosystem. Deep knowledge of various LLMs and techniques like prompt engineering, few-shot learning, and instruction tuning. Experience in building Agentic AI systems and coordinating multi-agent flows or tool-chaining. Familiarity with LLMOps/MLOps tools (e.g., MLflow, Weights & Biases, Kubeflow, SageMaker, or Vertex AI). Strong programming skills in Python, and experience deploying models using FastAPI, Flask, or Streamlit. Experience with cloud platforms (AWS/GCP/Azure) and handling GPU/TPU resources. Solid understanding of data structures, algorithms, and software engineering best Practices. Highly skilled AI/ML Engineer with a solid foundation in Machine Learning and deep hands-on experience in Generative AI (GenAI). Strong capabilities in building, training, and deploying ML models, along with significant experience. working with frameworks such as LangChain, LangGraph, and platforms like Hugging Face, vector databases, and various LLMs. Youll be a key contributor in developing smart assistants, AI agents, and ML solutions that solve complex business problems. Experience with LangSmith, PromptLayer, or other LLM observability tools Familiarity with Guardrails.AI, semantic caching, and output validation techniques Exposure to multi-modal models like CLIP, DALLE, Stable Diffusion, or Whisper Contributions to open-source GenAI or ML libraries/projects Domain expertise in areas like healthcare, finance, manufacturing, or legal tech.

Required Skills & Qualifications: - 57 years of industry experience building and deploying machine learning models. - Strong proficiency with machine learning algorithms including XGBoost, linear regression, and classification models. - Hands-on experience with AWS SageMaker for model development, training, and deployment. - Solid programming skills in Python (and relevant libraries such as scikit-learn, pandas, NumPy, etc.). - Strong understanding of model evaluation metrics, cross-validation, hyperparameter tuning, and performance optimization. - Experience in working with structured and unstructured datasets. - Knowledge of best practices in model deployment and monitoring in a production environment (ML Ops desirable). - Familiarity with tools like Docker, Git, CI/CD pipelines, and AWS ML services. - Excellent problem-solving skills, critical thinking, and attention to detail. - Strong communication and collaboration skills. Nice to Have: - Experience with additional AWS services like Lambda, S3, Step Functions, CloudWatch. - Exposure to deep learning frameworks like TensorFlow or PyTorch. - Familiarity with DataOps practices and agile methodologies. Mandatory Competencies Data Science - Machine learning Python - Numpy Data Science - Python Python - Panda Data Science - AWS Sagemaker

Project Role : Full Stack Engineer Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset. Must have skills : Data Science Good to have skills : NAMinimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Full Stack Engineer, you will be responsible for developing and engineering the end-to-end features of a system. Your typical day will involve collaborating with cross-functional teams to design and implement innovative solutions that enhance user experience and optimize backend processes. You will leverage new technologies to address complex business challenges while maintaining a cloud-first and agile approach, ensuring that the services provided to clients are continuously improved and aligned with their needs. Your role will require a balance of creativity and technical expertise to deliver high-quality software solutions that meet project requirements and client expectations. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Collaborate with team members to design and implement new features.- Conduct code reviews to ensure quality and adherence to best practices."Experience with Hugging Face Transformers, LangChain, OpenAI APIs Strong knowledge of machine learning libraries:scikit-learn, XGBoost, LightGBM Experience with Retrieval-Augmented Generation (RAG):Faiss, Pinecone, Weaviate, ChromaDB Training, fine-tuning, and optimizing transformer models (BERT, GPT, T5, LLaMA) Deep understanding of self-attention, positional embeddings, sequence modeling Strong NLP expertise:Named Entity Recognition (NER), topic modeling, text embeddings Good grasp of linear algebra:vectors, matrices, eigenvalues, eigenvectors etcExpertise in gradient descent, backpropagation, activation functions, loss functions Experience with dimensionality reduction techniques for feature selection Knowledge of time-series forecasting, anomaly detection, and probabilistic modeling Understanding of model serving techniques, including REST APIs and real-time inference""Develop and fine-tune LLMs (GPT, BERT, T5, LLaMA, Mistral) for text generation, summarization, translation, and question-answering tasks.Work with transformer-based architectures, understanding self-attention mechanisms, token embeddings, and model interpretability.Implement custom tokenization techniques, text embedding models (Sentence-BERT, OpenAI Embeddings, Cohere, etc.), and efficient inference optimizations.Apply prompt engineering and prompt tuning techniques to optimize model responses.Work with LangChain and LLM orchestration frameworks to build AI-powered applications.Build Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, Weaviate, ChromaDB.Work with Hugging Face Transformers, spaCy, NLTK, and OpenAI APIs." Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language).- Good To Have Skills: Experience with JavaScript frameworks such as React or Angular.- Strong understanding of RESTful API design and development.- Familiarity with cloud platforms such as AWS or Azure.- Experience with database management systems like MySQL or PostgreSQL."Must Have Skills: 1. Must have 5-7+ years of experience working as a Microsoft FED Angular.2. Strong understanding of software development principles, design patterns, and best practices.3. Develop, test, and maintain software applications using Angular and .NET.4. Designing & developing user interfaces using angular best practices5. Developing application code & unit tests in angular.6. Experience in consuming Web API/ Rest API using Javascript.7. Should have good troubleshooting and debugging skills Good to Have Skills: 1. Knowledge/Experience in Excel 2 Knowledge/Experience of Agile methodology and Sprint based project deliveryNice to Have Skills: 1. .Net Core2. Agile Development Methodology2. MySQL"" Should be good team player. Good Written & Verbal Communication skills Good analytical and troubleshooting skills." Additional Information:- The candidate should have minimum 3 years of experience in Python (Programming Language).- This position is based at our Bengaluru office.- A 15 years full time education is required.Resource should be open to work in B Shift (Afternoon Shifts 12:30 to 10:30) during week days. Qualification 15 years full time education

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU’LL BE DOING Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. Define technical architecture to productize Innovaccer’s machine-learning algorithms and take them to market with partnerships with different organizations Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. Work with customers and BI experts to build out reports and dashboards that are most useful to customers Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. Define and execute on the roadmap Requirements Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) 2+ years of experience in Data Science (healthcare experience will be a plus) Strong written and spoken communication skills Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. Good to have - knowledge of Sagemaker/Databricks Experience of containerizing models with Docker, Git, APIs, etc Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here’s What We Offer Generous Leave Benefits : Enjoy generous leave benefits of up to 40 days. Parental Leave : Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy : Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance : We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury. Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU’LL BE DOING Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. Define technical architecture to productize Innovaccer’s machine-learning algorithms and take them to market with partnerships with different organizations Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. Work with customers and BI experts to build out reports and dashboards that are most useful to customers Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. Define and execute on the roadmap Requirements Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) 2+ years of experience in Data Science (healthcare experience will be a plus) Strong written and spoken communication skills Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. Good to have - knowledge of Sagemaker/Databricks Experience of containerizing models with Docker, Git, APIs, etc Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here’s What We Offer Generous Leave Benefits : Enjoy generous leave benefits of up to 40 days. Parental Leave : Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy : Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance : We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury. Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

Greetings from Colan Infotech!! Role - Data Scientist Experience - 3-10 Years Job Location - Chennai/Bangalore Notice Period - Immediate to 30 Days Primary Skills Needed : AI/ML, Tensorflow, Django, Pytorch, NLP, Image processing,Gen AI,LLM Secondary Skills Needed : Keras, OpenCV, Azure or AWS Job Description:- Practical knowledge and working experience on Statistics and Operation Research methods. Practical knowledge and working experience in tools and frameworks like Flask, PySpark, Pytorch, tensorflow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j. Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc. Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models. Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database. Hands on experience on any version control tool (github, bitbucket). Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS Comprehend business issues and propose valuable business solutions. Design Factual or AI/profound learning models to address business issues. Design Statistical Models/ML/DL models and deploy them for production. Formulate what information is accessible from where and how to augment it. Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j Interested candidates send updated resume to kumudha.r@colanonline.com

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU'LL BE DOING ▶ Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. ▶ Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information ▶ Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. ▶ Define technical architecture to productize Innovaccer's machine-learning algorithms and take them to market with partnerships with different organizations ▶ Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. ▶ Work with customers and BI experts to build out reports and dashboards that are most useful to customers ▶ Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. ▶ Define and execute on the roadmap Requirements ▶ Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) ▶ 2+ years of experience in Data Science (healthcare experience will be a plus) ▶ Strong written and spoken communication skills ▶ Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) ▶ Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering ▶ Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. ▶ Good to have - knowledge of Sagemaker/Databricks ▶ Experience of containerizing models with Docker, Git, APIs, etc ▶ Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here's What We Offer Generous Leave Benefits: Enjoy generous leave benefits of up to 40 days. Parental Leave: Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy: Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance: We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

The technology that once promised to simplify patient care has brought more issues than anyone ever anticipated. At Innovaccer, we defeat this beast by making full use of all the data Healthcare has worked so hard to collect, and replacing long-standing problems with ideal solutions. We are looking for a Data Scientist with industry experience in applying a variety of machine learning solutions to real-world large-scale data to build intelligent systems. Healthcare background is a plus. Passion for travel can help you score some brownie points. THE THINGS YOU'LL BE DOING ▶ Design scalable solutions for real-time performance on a significantly large data set. Use big data technologies to optimally use infrastructure and improve performance. ▶ Build intelligent systems to capture and model the vast amount of behavioral data to enrich the content understanding with behavioral information ▶ Work with the business leaders and customers to understand their pain-points and build large-scale solutions for them. ▶ Define technical architecture to productize Innovaccer's machine-learning algorithms and take them to market with partnerships with different organizations ▶ Work with our data platform and applications team to help them successfully integrate the data science capability or algorithms in their product/workflows. ▶ Work with customers and BI experts to build out reports and dashboards that are most useful to customers ▶ Work with development teams to build tools for repeatable data tasks that will accelerate and automate development cycle. ▶ Define and execute on the roadmap Requirements ▶ Masters in Computer Science, Computer Engineering or other relevant fields (PhD Preferred) ▶ 2+ years of experience in Data Science (healthcare experience will be a plus) ▶ Strong written and spoken communication skills ▶ Strong hands-on experience in SQL and Python (Pandas, Scikit-learn) ▶ Experience working in classical ML techniques - XGboost, Clustering, Feature Engineering ▶ Experience in at least 1 Deep Learning frameworks like Pytorch/Tensorflow and and using LLMs in GenAI workflows. ▶ Good to have - knowledge of Sagemaker/Databricks ▶ Experience of containerizing models with Docker, Git, APIs, etc ▶ Ability to work with and influence multiple stakeholders and deliver solutions in a given time frame Benefits Here's What We Offer Generous Leave Benefits: Enjoy generous leave benefits of up to 40 days. Parental Leave: Experience one of the industry's best parental leave policies to spend time with your new addition. Sabbatical Leave Policy: Want to focus on skill development, pursue an academic career, or just take a break? We've got you covered. Health Insurance: We offer health benefits and insurance to you and your family for medically related expenses related to illness, disease, or injury Innovaccer is an equal-opportunity employer. We celebrate diversity, and we are committed to fostering an inclusive and diverse workplace where all employees, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, marital status, or veteran status, feel valued and empowered. Disclaimer Innovaccer does not charge fees or require payment from individuals or agencies for securing employment with us. We do not guarantee job spots or engage in any financial transactions related to employment. If you encounter any posts or requests asking for payment or personal information, we strongly advise you to report them immediately to our HR department at px@innovaccer.com. Additionally, please exercise caution and verify the authenticity of any requests before disclosing personal and confidential information, including bank account details. About Innovaccer Innovaccer activates the flow of healthcare data, empowering providers, payers, and government organizations to deliver intelligent and connected experiences that advance health outcomes. The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn fragmented data into proactive, coordinated actions that elevate the quality of care and drive operational performance. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure, extending the human touch in healthcare. For more information, visit www.innovaccer.com. Check us out on YouTube , Glassdoor , LinkedIn , Instagram , and the Web .

We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that is bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it? We understand that you are looking for growth and variety in your career at this point and we would love for you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We hire the best and trust them from day 1 to deliver global impact, handle teams and be responsible for the outcomes while our leaders support and mentor you. We are a profitable rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology. We offer global opportunities with fast-track careers while you work with a team that is fueled by purpose. The combination of these will lead to a truly differentiated experience for you. If this excites you, then apply below. Role: Senior Analyst - Data Science Descriptions: We are looking for a results-driven and hands-on Lead Data Scientist / Analyst with 5–6 years of experience to lead analytical solutioning and model development in the pharmaceutical commercial analytics domain. The ideal candidate will play a central role in designing and deploying Decision Engine frameworks, implementing advanced analytics solutions, and mentoring junior team members. Key Responsibilities: • Partner with cross-functional teams and client stakeholders to gather business requirements and translate them into robust ML/analytical solutions. • Design and implement Decision Engine workflows to support Next Best Action (NBA) recommendations in omnichannel engagement strategies. • Analyze large and complex datasets across sources like APLD, sales, CRM, call plans, market share, patient claims, and segmentation data. • Perform ad hoc and deep-dive analyses to address critical business questions across commercial and medical teams. • Develop, validate, and maintain predictive models for use cases such as patient journey analytics, HCP targeting, sales forecasting, risk scoring, and marketing mix modeling. • Implement MLOps pipelines using Dataiku, Git, and AWS services to support scalable and repeatable deployment of analytics models. • Ensure data quality through systematic QC checks, test case creation, and validation frameworks. • Lead and mentor junior analysts and data scientists in coding best practices, feature engineering, model interpretability, and cloud-based workflows. • Stay up to date with industry trends, regulatory compliance, and emerging data science techniques relevant to life sciences analytics. • 5+ years of hands-on experience in pharmaceutical commercial analytics, with exposure to cross-functional brand analytics, omnichannel measurement, and ML modeling. • At least 3 years of experience developing and deploying predictive models and ML pipelines in real-world settings. • Proven experience with data platforms such as Snowflake, Dataiku, AWS, and proficiency in PySpark, Python, and SQL. • Experience with MLOps practices, including version control, model monitoring, and automation. • Strong understanding of pharmaceutical data assets (e.g., APLD, DDD, NBRx, TRx, specialty pharmacy, CRM, digital engagement). • Proficiency in ML algorithms (e.g., XGBoost, Random Forest, SVM, Logistic Regression, Neural Networks, NLP). • Experience in key use cases: Next Best Action, Recommendation Engines, Attribution Models, Segmentation, Marketing ROI, Collaborative Filtering. • Hands-on expertise in building explainable ML models and using tools for model monitoring and retraining. • Familiarity with dashboarding tools like Tableau or PowerBI is a plus. • Strong communication and documentation skills to effectively convey findings to both technical and non-technical audiences. • Ability to work in a dynamic, fast-paced environment and deliver results under tight timelines. Indegene is proud to be an Equal Employment Employer and is committed to the culture of Inclusion and Diversity. We do not discriminate on the basis of race, religion, sex, colour, age, national origin, pregnancy, sexual orientation, physical ability, or any other characteristics. All employment decisions, from hiring to separation, will be based on business requirements, the candidate’s merit and qualification. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristics.

🚀 About the Project We’re partnering with a U.S.-based trading firm running three profitable Nasdaq-100 (NQ) futures strategies . Your job: Build AI models that decide when to trade and which strategy to deploy — backed by real capital, not paper simulations. This isn’t a research project. Your models will go live after validation. ⚙️ What You’ll Build ✅ Binary Classification Model: Trade vs No-Trade (Target: 65%+ accuracy) ✅ Multi-Class Model: Strategy A / B / C selection ✅ Market Regime Detection: Identify which strategies thrive under what conditions ✅ Daily Prediction Pipeline: Fully automated model deployment ✅ Walk-Forward Validation: 2021–2025 rolling testing — no leakage, no shortcuts 🧪 What Sets This Role Apart Live trade logs, real strategy data (not simulations) Models control real-money trades Must beat baseline ("always trade Strategy A") Advanced walk-forward testing and lookback window optimization required Real-time market data from VIX, NDX, SPX, FOMC days, CPI, etc. 🧰 Tech Requirements (Non-Negotiable) Python (pandas, scikit-learn, XGBoost/LightGBM) Time series modeling, regime detection, overfitting prevention Strong grasp of walk-forward validation vs k-fold Interpretability: You must explain why the model makes decisions API/data integration: Yahoo Finance, FRED, macro & sentiment indicators Versioning: Git workflow for all code & models 📅 Timeline & Milestones Week 1: Data ingestion + regime analysis Week 2: Model building (binary + multi-class) Week 3: Walk-forward validation + optimization Week 4: Deployment script + full documentation 🎯 Success Criteria ✅ 65%+ accuracy (both models) ✅ 60%+ Sharpe ratio improvement ✅ No data leakage ✅ Regime-aware insights ✅ Daily prediction automation 👤 Ideal Candidate 8+ years in ML/AI with proven financial trading experience Strong portfolio of trading optimization projects Deep understanding of market regimes , behavioral biases, and risk metrics Can defend your code, logic, and decisions in technical interviews 📑 How to Apply 📩 Send us: Your trading ML portfolio (must show strategy optimization) Your walk-forward validation approach A previous client reference for a similar ML trading project How you'll prevent overfitting in this specific use case ❌ Please Don’t Apply If: You only have general ML experience (no trading) You’ve only worked on banking/fintech platforms, not predictive models You can’t explain regime detection or validation integrity 📢 Join us at OPIN Solutions to build AI that directly impacts real trades. This project has high visibility and could lead to an ongoing optimization role with the client. #Hiring #AI #MachineLearning #QuantTrading #AlgoTrading #FinancialML #NQFutures #TradingJobsIndia #RemoteWork #OPINSolutions

A strong level of proficiency in python programming. Practical knowledge and working experience on Statistics and Operation Research methods. Practical knowledge and working experience in tools and frameworks like Flask, PySpark,Pytorch,tensorflow, keras, Databricks, OpenCV, Pillow/PIL, streamlit, d3js, dashplotly, neo4j. Hands on experience in Analytics/AI-ML AWS services like Sagemaker, Canvas, Bedrock. Good understanding of how to apply predictive and machine learning techniques like regression models, XGBoost, random forest, GBM, Neural Nets, SVM etc. Proficient with NLP techniques like RNN, LSTM and Attention based models and effectively handle readily available stanford, IBM, Azure, Open AI NLP models. Good understanding of SQL from a perspective of how to write efficient queries for pulling the data from database. Hands on experience on any version control tool (github, bitbucket). Experience of deploying ML models into production environment experience (MLOps) in any one of the cloud platforms like Azure and AWS. Understanding business needs / mapping it to the business processes. Hands on experience in agile project delivery. Good in conceptualizing and visualizing end to end business needs both at high level as well as detailed. Good in articulating the business needs. Good analytical and problem-solving skills. Good communication, listening and probing skills. Strong inter-personnel skills. Should collaborate with other team members and work as team. Job Description: Comprehend business issues and propose valuable business solutions. Design Factual or AI/profound learning models to address business issues. Design Statistical Models/ ML/DL models and deploy them for production. Formulate what information is accessible from where and how to augment it. Develop innovative graphs for data comprehension using d3js, dashplotly and neo4j. Preferred Certification: (Good to have) AWS Specialty Certification in Data Analytics, Machine Learning.

Machine Learning Engineer (L1) Experience Required: 2-4 years As a Machine Learning Engineer at Spring, you’ll help bring data-driven intelligence into our products and operations. You’ll support the development and deployment of models and pipelines that power smarter decisions, more personalized experiences, and scalable automation. This is an opportunity to build hands-on experience in real-world ML and AI systems while collaborating with experienced engineers and data scientists. You’ll work on data processing, model training, and integration tasks — gaining exposure to the entire ML lifecycle, from experimentation to production deployment. You’ll learn how to balance model performance with system requirements, and how to structure your code for reliability, observability, and maintainability. You’ll use modern ML/AI tools such as scikit-learn, HuggingFace, and LLM APIs — and be encouraged to explore AI techniques that improve our workflows or unlock new product value. You’ll also be expected to help build and support automated data pipelines, inference services, and validation tools as part of your contributions. You’ll work closely with engineering, product, and business stakeholders to understand how models drive value. Over time, you’ll build the skills and judgment needed to identify impactful use cases, communicate technical trade-offs, and contribute to the broader evolution of ML at Spring. What You’ll Do Support model development and deployment across structured and unstructured data and AI use cases. Build and maintain automated pipelines for data processing, training, and inference. Use ML and AI tools (e.g., scikit-learn, LLM APIs) in day-to-day development. Collaborate with engineers, data scientists, and product teams to scope and deliver features. Participate in code reviews, testing, and monitoring practices. Integrate ML systems into customer-facing applications and internal tools. Identify differences in data distribution that could affect model performance in real-world applications. Stay up to date with developments in the machine learning industry. Tech Expectations Core Skills Curiosity, attention to detail, strong debugging skills, and eagerness to learn through feedback Solid foundation in statistics and data interpretation Strong understanding of data structures, algorithms, and software development best practices Exposure to data pipelines, model training and evaluation, or training workflows Languages Must Have: Python, SQL ML Algorithms Must Have: Traditional modeling techniques (e.g., tree models, Naive Bayes, logistic regression) Ensemble methods (e.g., XGBoost, Random Forest, CatBoost, LightGBM) ML Libraries / Frameworks Must Have: scikit-learn, Hugging Face, Statsmodels, Optuna Good to Have: SHAP, Pytest Data Processing / Manipulation Must Have: pandas, NumPy Data Visualization Must Have: Plotly, Matplotlib Version Control Must Have: Git Others – Good to Have AWS (e.g., EC2, SageMaker, Lambda) Docker Airflow MLflow Github Actions

About Us: Red & White Education Pvt. Ltd., established in 2008, is Gujarats top NSDC & ISO-certified institute focused on skill-based education and global employability. Role Overview: Were hiring a full-time Onsite AI, Machine Learning, and Data Science Faculty/ Trainer with strong communication skills and a passion for teaching, Key Responsibilities: Deliver high-quality lectures on AI, Machine Learning, and Data Science . Design and update course materials, assignments, and projects. Guide students on hands-on projects, real-world applications, and research work. Provide mentorship and support for student learning and career development. Stay updated with the latest trends and advancements in AI/ML and Data Science. Conduct assessments, evaluate student progress, and provide feedback. Participate in curriculum development and improvements. Skills & Tools: Core Skills: ML, Deep Learning, NLP, Computer Vision, Business Intelligence, AI Model Development, Business Analysis. Programming: Python, SQL (Must), Pandas, NumPy, Excel. ML & AI Tools: Scikit-learn (Must), XGBoost, LightGBM, TensorFlow, PyTorch (Must), Keras, Hugging Face. Data Visualization: Tableau, Power BI (Must), Matplotlib, Seaborn, Plotly. NLP & CV: Transformers, BERT, GPT, OpenCV, YOLO, Detectron2. Advanced AI: Transfer Learning, Generative AI, Business Case Studies. Education & Experience Requirements: Bachelor's/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field. Minimum 1+ years of teaching or industry experience in AI/ML and Data Science. Hands-on experience with Python, SQL, TensorFlow, PyTorch, and other AI/ML tools. Practical exposure to real-world AI applications, model deployment, and business analytics. For further information, please feel free to contact 7862813693 us via email at career@rnwmultimedia.edu.in Job Types: Full-time, Permanent Pay: ₹30,000.00 - ₹35,000.00 per month Benefits: Flexible schedule Leave encashment Paid sick time Paid time off Provident Fund Schedule: Day shift Supplemental Pay: Performance bonus Yearly bonus Work Location: In person

Experience : 2.00 + years Salary : INR 1500000-2500000 / year (based on experience) Expected Notice Period : 30 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Office (Pune) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Anervea.AI) (*Note: This is a requirement for one of Uplers' client - Anervea.AI) What do you need for this opportunity? Must have skills required: Airflow, LLMs, NLP, Statistical Modeling, Predictive Analysis, Forecasting, Python, SQL, MLFlow, pandas, Scikit-learn, XgBoost Anervea.AI is Looking for: As an ML / Data Science Engineer at Anervea, you’ll work on designing, training, deploying, and maintaining machine learning models across multiple products. You’ll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. You’ll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required : Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering, model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes : Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomes—not just code Bonus Qualities : Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Senior Data Scientist Location: Remote (Sri Lanka or Global – flexible timezone overlap preferred) Type: Full-time Salary: $4,000 – $6,000/month Company: Huex About Huex Huex helps global companies build high-performance product teams using Sri Lanka’s top 3%™ talent , enhanced by our proprietary aiBoost™ framework . From healthcare and fintech to real estate and AI startups, our teams deliver scalable, innovative solutions at startup speed. We’re now looking for a Senior Data Scientist to lead high-impact data science projects across our client base—building intelligent systems, AI-integrated features, and performance-driven models that accelerate decision-making and product outcomes. What You’ll Be Doing Design, develop, and deploy ML models and data pipelines for real-world client applications Build recommendation engines, scoring systems, and predictive tools using behavioral and transactional data Collaborate with product, engineering, and design teams to embed data intelligence directly into customer-facing platforms Leverage AI tools (e.g., LLMs, embeddings, OpenAI APIs) to automate content, messaging, or decision-making flows Create dashboards and insights that drive decisions for clients and internal teams Mentor junior data professionals and contribute to internal documentation and best practices Work on a wide range of projects, from PoCs to production-ready models, across industries like proptech, healthtech, and retail Tools & Tech Stack Languages: Python, SQL ML/NLP Libraries: scikit-learn, XGBoost, HuggingFace, TensorFlow, PyTorch Data Engineering: Pandas, Airflow, DBT, Postgres, Snowflake Visualization: Looker, Streamlit, Power BI, or Metabase Bonus: Experience with LLM APIs, vector databases, or prompt engineering Must-Have Qualifications 5+ years of experience as a data scientist or ML engineer in production environments Strong grasp of data modeling, statistics, and experimentation Experience building and deploying end-to-end ML pipelines Excellent communication skills to work cross-functionally with remote teams and clients Ability to manage multiple projects and ship high-quality work under tight timelines Bonus Points Experience working in B2B SaaS, early-stage startups, or agency-style project settings Exposure to AI-powered automation tools like ChatGPT, Claude, or Midjourney Comfort working with product managers, marketers, and non-technical stakeholders Why Join Huex? Collaborate with elite teams across 20+ global markets Work on high-impact projects across industries Leverage AI and automation to increase your effectiveness Learn, grow, and contribute to the next generation of AI-native teams Flexible remote culture, high trust, and performance-first mindset

Job Title: AI/ML Engineer Experience: 4+ Years Location: Remote Job Type: Full-Time Job Summary: We are looking for a passionate and results-driven AI/ML Engineer with 4 years of experience in designing, building, and deploying machine learning models and intelligent systems. The ideal candidate should have solid programming skills, a strong grasp of data preprocessing, model evaluation, and MLOps practices. You will collaborate with cross-functional teams including data scientists, software engineers, and product managers to integrate intelligent features into applications and systems. Key Responsibilities: Design, develop, train, and optimize machine learning and deep learning models for real-world applications. Preprocess, clean, and transform structured and unstructured data for model training and evaluation. Implement, test, and deploy models using APIs or microservices (Flask, FastAPI, etc.) in production environments. Use ML libraries and frameworks like Scikit-learn, TensorFlow, PyTorch, Hugging Face, XGBoost, etc. Monitor and retrain models as needed for performance, accuracy, and drift mitigation. Collaborate with software and data engineering teams to operationalize ML solutions using MLOps tools. Stay updated with emerging trends in AI/ML and suggest enhancements to existing systems. Required Skills and Qualifications: Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, Data Science, or related field. 4+ years of hands-on experience in machine learning model development and deployment. Strong experience in Python and libraries like Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in model deployment using Flask, FastAPI, Docker, and REST APIs. Experience with version control (Git), model versioning, and experiment tracking (MLflow, Weights & Biases). Familiarity with cloud platforms like AWS (SageMaker), Azure ML, or GCP AI Platform. Knowledge of databases (SQL/NoSQL) and data pipelines (Airflow, Spark, etc.). Strong problem-solving and debugging skills, with an analytical mindset.

Organization Overview: ML Solutions team within Markets OPS Technology is dedicated to developing solutions using Artificial Intelligence, Machine Learning and Generative AI. This team is a leader in creating new ideas, innovative technology solutions, and ground-breaking solutions for Markets Operations and Other Line of Businesses. We work closely with our clients and business partners to progress solutions from ideation to production by leveraging the entrepreneurial spirit and technological excellence. Job Description: ML Solutions team is seeking a highly skilled and experienced Data Analytics/Machine Learning Engineer with a strong background in developing and deploying AI/ML models and Gen AI based solutions. In this hands-on role, you will be responsible for taking AI models from concept to production, utilizing traditional AI, generative AI and Large Language Models. You will collaborate closely with business partners and stakeholders to introduce and embrace these advanced technologies, elevating client experiences, delivering value to our customers, and ensuring regulatory compliance through cutting-edge technology solutions. Key Responsibilities: Hands-On Execution and Delivery: Actively contribute to the development and delivery of AI solutions, driving innovation and excellence within the team. Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks. Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation. Research and Development: Participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field. Cross-Functional Collaboration: Collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services. 2-4 years of relevant experience Skills & Qualifications: Strong hands-on experience in Machine Learning, delivering complex solutions to production. Experience with Generative AI technologies essential. Knowledge of NLP, Name Entity Recognition In-depth knowledge of deep learning and Generative AI frameworks such as, Langchain, Lang Graph, Crew AI or similar. Experience with and other open-source frameworks/ libraries/ APIs like Hugging Face Transformers, Spacy, Pandas, scikit-learn, NumPy. Experience in using Machine Learning/Deep Learning: XGBoost, LightGBM, TensorFlow, PyTorch. Proficiency in Python Software Development, following Object-Oriented design patterns and best practices. Strong background in mathematics: linear algebra, probability, statistics, and optimization. Experience with evaluation, scoring with framework like ML Flow Experience of Docker container and edited a Docker file, experience with K8s is a plus. Experience with Postgres and Vector DBs a plus. Excellent problem-solving skills and the ability to think creatively. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams Publications and contributions to the AI research community are a plus. Bachelor’s/Master’s degree or equivalent experience in Computer Science, Data Science, Statistics, or a related field. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster.

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description About the Team The Finance Analytics & Insights (FA&I) team is transforming how Finance operates by embedding AI/ML into the core of our decision-making processes. We are building intelligent, scalable data products that power use cases across forecasting, anomaly detection, case summarization, and agentic automation. Our global team includes data product managers, analysts, and engineers who are passionate about delivering measurable business value. Role Overview We are seeking a highly motivated and analytically strong ML Engineer to join our India-based team. This role will support the development and scaling of AI/ML-powered data products that drive strategic insights across Finance. As an IC3-level individual contributor, you will work closely with the Data Product Manager and Insights Analyst to build AI/ML solutions that deliver measurable business value. Key Responsibilities Design, build, and deploy machine learning models that support use cases such as: Forecasting Anomaly detection Case summarization Agentic AI assistants Partner with the Insights Analyst to perform feature engineering, exploratory data analysis, and hypothesis testing Build and iterate on proof-of-concepts (POCs) to validate model design and demonstrate business value Collaborate with the Data Product Manager to align model development with product strategy and business outcomes Own and manage the Databricks instance for the FA&I team—partnering with the DT Data & Analytics team to define a roadmap of capabilities, test and validate new features, and ensure the platform supports scalable ML development and deployment Ensure models are production-ready, scalable, and maintainable—working closely with DT and D&A teams to integrate into enterprise platforms Monitor model performance, implement feedback loops, and retrain models as needed Contribute to agile product development processes including sprint planning, backlog grooming, and user story creation Qualifications Required Skills & Experience 3–5 years of experience in machine learning engineering, data science, or applied AI roles Strong proficiency in Python and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch) Solid understanding of feature engineering, model evaluation, and MLOps practices Experience working with large datasets using SQL and Snowflake Familiarity with Databricks for model development and orchestration Experience with CI/CD pipelines, version control (Git), and ML workflow tools Ability to translate business problems into ML solutions and communicate technical concepts to non-technical stakeholders Experience working in agile teams and collaborating with product managers, analysts, and engineers Preferred Qualifications Experience working in or supporting Finance or Accounting teams Prior experience deploying models in production environments and integrating with enterprise systems Familiarity with GenAI, prompt engineering, or LLM-based applications is a plus Experience with MLflow, Azure ML, or similar platforms Comfort with async collaboration tools and practices, including Teams, recorded video demos, and documentation-first communication Experience working in a global, cross-functional environment with stakeholders across time zones Key Behaviors & Mindsets Builder’s Mentality: You love turning ideas into working models and iterating quickly to improve them. Collaborative Engineer: You work closely with analysts and product managers to co-create solutions that solve real business problems. Customer-Centric: You care deeply about the end user and build models that are interpretable, actionable, and aligned with business needs. Bias for Action: You move fast, test often, and focus on delivering value—not just code. Global Mindset: You thrive in a distributed team and proactively align to US morning hours (PST overlap) to keep momentum across geographies. Async-First Communicator: You’re comfortable working in a hybrid async environment—leveraging Teams, recorded demos, and documentation to keep work moving forward. Growth-Oriented: You’re always learning—whether it’s a new algorithm, tool, or business domain—and you help others grow too. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

BugRaid AI is reimagining how engineering teams handle incidents — with a powerful blend of AI agents, traditional machine learning, and modern observability pipelines. We’re seeking an AI Engineer who excels at the intersection of infrastructure and intelligence — someone who enjoys solving complex technical problems with practical models that perform well in real-world scenarios. Location: Remote Preference: Hyderabad / Bangalore candidates only Type: Full-time | ESOPs + Salary Experience: 2+ years Immediate joiners only preferred Responsibilities Impactful Machine Learning: Apply and scale models like Random Forest, DBSCAN, KNN, and GNNs to understand noisy logs, alerts, and metrics in real-time and batch. Agent Intelligence : Develop lightweight reasoning agents that assist SREs in debugging, resolving, and predicting incidents. AI Agent Architecture: Design LLM-powered agents for logs, metrics, traces, and incident resolution. Prompt Engineering & Tooling: Create advanced function-calling and reasoning workflows for multi-step execution. Zero Data Retention Architecture: All data is read-only, secure, and compliant (PII, GDPR, PCI DSS) — your work resides within ephemeral AWS-native environments. Infrastructure-Aware ML: Collaborate closely with our AWS stack (Lambda, ECS, Kinesis, S3, Bedrock) to ensure scalable, secure models that serve with low latency. Feedback Loops & Fine-Tuning: Incorporate real-time signal feedback and model evaluation for precise incident response. Collaborative Development: Partner with backend and infrastructure engineers to deploy models as microservices and REST endpoints seamlessly. Data Analysis: Evaluate quality, clean, and structure raw data for downstream processing. Design scalable and accurate prediction algorithms. Collaborate with engineering teams to transition analytical prototypes into production-ready systems. Generate actionable insights to improve business operations. Qualifications Bachelor's degree or equivalent experience in a quantitative field (Computer Science, Engineering, etc.) 2+ years of practical ML experience Experience with Random Forest, DBSCAN, KNN, GNN (Graph Neural Networks) Proficiency in Python and ML libraries such as scikit-learn, XGBoost, PyTorch. Experience with RLHF, LangChain, or open-source agentic libraries Comfort with AWS services (Lambda, ECS, Kinesis, S3, SageMaker, Bedrock) Experience in log analysis, anomaly detection, or observability systems is a big plus Strong debugging skills and systems-level thinking At least 1-2 years in quantitative analytics or data modeling Deep understanding of predictive modeling, machine learning, clustering, classification techniques, and algorithms Proficiency in a programming language (Python, JavaScript) Knowledge of Big Data frameworks and visualization tools (preferred) Why Join BugRaid.AI We’re building a groundbreaking AI incident response platform. Remote-first team, open feedback loops, and high trust culture. Shareholding opportunities with meaningful equity and ownership of key AI pipeline components. Backed by real customers in our beta stage, we are addressing practical operational challenges. Ready to help redefine how AI manages software failures? 📩 Send your resume or LinkedIn profile to manoj.bhamidipati@bugraid.ai or DM me.

Job Description – Data Scientist– Credit Risk Modelling Domain: Retail Banking / Credit Cards Location: Mumbai Experience: 3–5 years Industry: Banking / Financial Services Why would you like to join us? TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, the US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit www.transorg.com to learn more about us. What do we expect from you?  Build and validate credit risk models, including application scorecards and behavior scorecards (B-score), aligned with business and regulatory requirements.  Use advanced machine learning algorithms such as Logistic Regression, XGBoost, and Clustering to develop interpretable and high-performance models.  Translate business problems into data-driven solutions using robust statistical and analytical methods.  Collaborate with cross-functional teams, including credit policy, risk strategy, and data engineering, to ensure effective model implementation and monitoring.  Maintain clear, audit-ready documentation for all models and comply with internal model governance standards.  Track and monitor model performance, proactively suggesting recalibrations or enhancements as needed. What do you need to excel at?  Writing efficient and scalable code in Python, SQL, and PySpark for data processing, feature engineering, and model training.  Working with large-scale structured and unstructured data in a fast-paced banking or fintech environment.  Deploying and managing models using MLFlow, with a strong understanding of version control and model lifecycle management.  Understanding retail banking products, especially credit card portfolios, customer behavior, and risk segmentation.  Communicating complex technical outcomes clearly to non-technical stakeholders and senior management.  Applying a structured problem-solving approach and delivering insights that drive business value. What are we looking for?  Bachelor’s or master’s degree in Statistics, Mathematics, Computer Science, or a related quantitative field.  3–5 years of experience in credit risk modelling, preferably in retail banking or credit cards.  Hands-on expertise in Python, SQL, PySpark, and experience with MLFlow or equivalent MLOps tools.  Deep understanding of machine learning techniques, including Logistic Regression, XGBoost, and Clustering.  Proven experience in developing Application Scorecards and behavior Scorecards using real- World Banking Data.  Strong documentation and compliance orientation, with an ability to work within regulatory frameworks.  Curiosity, accountability, and a passion for solving real-world problems using data.  Cloud Knowledge, JIRA, GitHub(good to have)