175 Model Monitoring Jobs - Page 3

As a Software Engineer III at JPMorgan Chase within the Consumer and Community Banking - Data Technology, you will be a seasoned member of an agile team, tasked with designing and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. Your responsibilities will include implementing critical technology solutions across multiple technical areas, supporting various business functions to achieve the firm's business objectives. - Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems - Creates secure and high-quality...

Role Overview We are seeking an experienced MLOps Engineer to architect, automate, and govern ML model operations across the entire lifecycle at scale. Responsibilities: Manage full ML lifecycle: data prep, feature pipelines, training, deployment, monitoring and retraining automation and model governance. Design and implement CI/CD pipelines with Docker, Kubernetes/ECS, Terraform/CloudFormation. Build scalable ETL/ELT workflows (batch & streaming) using PySpark, Airflow, SQL tuning & partitioning. Develop model retraining triggers using monitoring signals (data drift, concept drift, performance decay). Implement end-to-end observability for model/API health (Prometheus, Grafana, ELK, CloudWa...

**Role Overview:** As a part of the Citi Analytics & Information Management (AIM) team, you will be leading the Financial Crimes & Fraud Prevention Analytics in the Fraud Operation team based in Pune/Bangalore. Reporting to the Director/Managing Director, AIM, your primary responsibility will be to lead a team of data scientists in developing and implementing Machine Learning (ML) / AI / Gen AI models for fraud prevention. You will collaborate with the model implementation team, ensure model documentation, and contribute to achieving overall business goals by analyzing data and developing effective models. **Key Responsibilities:** - Lead as Subject Matter Expert (SME) in ML/AI/Gen AI, with ...

As a Senior Analyst or Machine Learning Engineer at Tiger Analytics, you will have the opportunity to work on cutting-edge data analytics and machine learning problems across various industries. Your typical day will involve: - Engaging with clients to understand their business context. - Translating business problems and technical constraints into technical requirements for the desired analytics solution. - Collaborating with a team of data scientists and engineers to integrate AI and analytics into business decision processes. We expect you to have the following qualifications and skills: - 3+ years of experience with at least 1+ years of relevant Data Science experience. - Proficient in s...

As an AI/ML Specialist at our company, you will be part of a dynamic team that values talent and innovation. Your role will involve designing, developing, and deploying AI and machine learning models for real-world applications. You will work with large datasets, optimize AI-driven solutions, and stay updated with industry trends to enhance model efficiency. If you are passionate about AI and machine learning, and eager to work on cutting-edge technology, we encourage you to apply. **Responsibilities:** - Design, develop, and deploy AI and machine learning models for real-world applications. - Train, test, troubleshoot, and fine-tune machine learning models to enhance accuracy and performanc...

Conduct independent validations of models, including but not limited to credit risk, market risk, counterparty credit risk, fraud detection, Stress Testing, AML and forecasting models. Should have model validation exposure in at least 2-3 of the areas listed above. Assess conceptual soundness, data quality, implementation accuracy, and performance of models. Prepare comprehensive validation reports detailing findings, methodologies, and recommendations. Document validation processes to ensure transparency and compliance with regulatory requirements. Ensure models adhere to relevant guidelines such as SR 11-7, EBA 2017/16, CCAR, Basel III, and other applicable standards.

As a Machine Learning Engineer at Giggso, your role involves building and productizing robust machine learning models to ensure high performance in production environments. You will design and implement systems for model monitoring, performance drift detection, and automated collaboration with cross-functional teams. Additionally, you will apply Natural Language Processing (NLP) techniques to real-world problems and ensure solutions adhere to security, compliance, and governance standards. Your key responsibilities will include: - Building and productizing robust machine learning models for high performance in production environments. - Designing and implementing systems for model monitoring...

As a Data and Analytics professional at Standard Chartered in Bangalore, your role will involve monitoring credit risk IRB and IFRS9 models for the measurement of PD, EAD and LGD for the bank's retail portfolios. You will be responsible for working on the end-to-end model monitoring cycle, from data gathering and cleansing to documentation and presentations to key stakeholders. Your key responsibilities will include: - Elevating the current monitoring outputs to best-in-class by adding analytical insights - Ensuring that all monitoring results and analysis comply with the Group monitoring standards In addition, you will need to understand Model related uncertainty risks such as data, regulat...

Become part of Barclays Impairment team as an Assistant Vice President - Impairment US Cards Portfolio Analytics. At Barclays, we don't just anticipate the future we're creating it. As a part of this role , the candidate will be required to embed a control functionality by building and leading the development of the output for the team ,where you will help the colleague to demonstrate analytical and technical skills as well as knowledge of fundamentals of retail credit risk management, particularly across impairment management. The colleague will also need to demonstrate sound judgement in collaboration with the wider team and management. To Be Successful In This Role, You Should Have To pro...

Interested can whatsapp me at 6369973379 or email your resume @ shankara.rajesh@tigeranalytics.com The successful candidate will join the Model Risk Management and Validation Group (MRM&V). MRM&V performs independent analytical reviews and validations of all models throughout the Bank. The candidate will perform analysis of quantitative models and other tools through extensive reviews into how the models was developed and how it functions. The candidate will also provide written communications of their findings in a clear, succinct manner to all model stakeholders including model owners, developers, lines of business, audit and regulatory agencies. By the nature of this position, the success...

Become part of Barclays Impairment team as an Assistant Vice President - Impairment US Cards Portfolio Analytics. At Barclays, we don't just anticipate the future we're creating it. As a part of this role , the candidate will be required to embed a control functionality by building and leading the development of the output for the team ,where you will help the colleague to demonstrate analytical and technical skills as well as knowledge of fundamentals of retail credit risk management, particularly across impairment management. The colleague will also need to demonstrate sound judgement in collaboration with the wider team and management. To Be Successful In This Role, You Should Have To pro...

Fincrime AML Model Analyst/Developer (3 – 5 Years) Job Summary: We are seeking a dedicated professional for the Financial Crime Model developer role. This position is responsible for the development and maintenance of all AML Feeder models, ensuring adherence to acceptable model risk practices and defined performance parameters. The successful candidate will play a critical role in enhancing the firm’s AML risk coverage while ensuring the operational viability of the models. This role requires a strong understanding of financial crime analytics and a commitment to maintaining high standards in model performance and compliance. Key Responsibilities: • Risk Analytics & Modeling: Develop and im...

You are an experienced Data Scientist with expertise in ML/DL, model lifecycle management, and MLOps tools such as MLflow and Kubeflow. You are proficient in Python, TensorFlow, PyTorch, Scikit-learn, and Hugging Face models. Your strong experience in NLP, fine-tuning transformer models, and dataset preparation will be valuable. Key Responsibilities: - Design and implement end-to-end ML pipelines from data ingestion to production - Develop, fine-tune, and optimize ML models for high performance and scalability - Compare and evaluate models using key metrics such as F1-score, AUC-ROC, and BLEU - Automate model retraining, monitoring, and drift detection - Collaborate with engineering teams to...

As a Data Scientist at our company, you will be responsible for supporting the development and deployment of machine learning models and analytics solutions aimed at improving decision-making across the mortgage lifecycle. Your key responsibilities will include: - Developing and maintaining machine learning models and statistical tools for various use cases such as risk scoring, churn prediction, segmentation, and document classification. - Collaborating with Product, Engineering, and Analytics teams to identify data-driven opportunities and support automation initiatives. - Translating business questions into modeling tasks and contributing to the design of experiments and success metrics. ...

About the Role We are looking for a Model Deployment Engineer to operationalize machine learning models and ensure their scalable, reliable, and efficient deployment in production environments. The ideal candidate will bridge the gap between data science and engineering, focusing on deploying, monitoring, and maintaining ML/AI models while ensuring high performance and robustness. Key Responsibilities Deploy machine learning models into production environments, ensuring scalability, reliability, and performance. Collaborate with data scientists, ML engineers, and software developers to understand model requirements and system constraints. Design and implement APIs, microservices, or containe...

Design, deploy & monitor ML pipelines on GCP using Vertex AI, Dataflow, BigQuery. Migrate on-prem/Hadoop models to GCP. Implement Feature Store, MLflow tracking, & post-model monitoring for Data & Model Drift. Required Candidate profile 4–9 yrs of hands-on experience in MLOps using Python, Spark/PySpark, and GCP. Skilled in CI/CD, Docker, Terraform, and ML pipeline automation for model deployment, monitoring, and retraining.

**Job Description:** As a C14 (People Manager) in the Financial Crimes & Fraud Prevention Analytics Model Development team at Citi Analytics & Information Management (AIM) based in Pune, India, you will play a crucial role in leading a team of 15+ data scientists. Your primary responsibility will be to oversee the successful development and implementation of Machine Learning (ML), Artificial Intelligence (AI), and Generative AI models on various platforms to mitigate fraud losses and minimize customer impact. You will work closely with the model implementation team, ensure model documentation, and address questions from model risk management (MRM) while adapting to business needs. Additional...

What youll do? Lead and mentor a team of data scientists/analysts Provide analytical insights by analyzing various types of data, including mining our customer data, review of relevant cases/samples, and incorporation of feedback from others. Work closely with business partners and stakeholders to determine how to design analysis, testing, and measurement approaches that will significantly improve our ability to understand and address emerging business issues. Produce intelligent, scalable, and automated solutions by leveraging Data Science skills. Work closely with Technology teams on development of new capabilities to define requirements and priorities based on data analysis and business k...

The Opportunity As the Global Practice Lead AI, you will lead the global strategy, development, and delivery of AI solutions centered around Nutanix Enterprise AI (NAI). This role demands deep expertise in generative AI, LLMOps, and hybrid cloud architectures, with a strong focus on operational simplicity, scalability, and enterprise-grade security. You will drive innovation, build high-performing practice team spanning across geos, and ensure successful client outcomes across industries. The Global Practice Lead for AI is expected to bring a strong foundation in deep expertise in delivering enterprise-grade AI solutions across industries especially in terms of the infrastructure needs in AI...

As a Data Scientist at Lifease Solutions LLP, your main responsibility will be to develop machine learning and deep learning models for predicting match scores & outcomes, team & player performances, and statistics. You will also be involved in in-depth cricket analytics to analyze player form, team strengths, matchups, and opposition weaknesses. Additionally, you will work on data processing & engineering tasks, model deployment & MLOps, and performance metrics & model explainability. Key Responsibilities: - Develop ML/DL models for predicting match scores & outcomes, team & player performances, and statistics. - Implement time-series forecasting models (LSTMs, Transformers, ARIMA, etc.) fo...

As an Associate Director with 12-15 years of experience in data sciences and data mining, with a minimum of 2 years of hands-on experience working on Vertex AI, your role at KPMG in India will involve leading projects, designing scalable data solutions, driving the adoption of AI and machine learning practices within the organization, and supporting pre-sales activities. You will be based in Bangalore and will be responsible for architecting and implementing end-to-end data analytics solutions using Google Cloud services such as BigQuery, Dataflow, Pub/Sub, and Cloud Storage. - Architect and Implement: - Design and implement end-to-end data analytics solutions using Google Cloud services suc...

Embark on a transformative journey as a Data Scientist AI/ML - AVP at Barclays in the Group Control Quantitative Analytics team, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. Group Control Quantitative Analytics (GCQA) is a global organization of highly specialized data scientists working on Artificial Intelligence, Machine Learning and Gen AI model development and model management including governance and monitoring. GCQA is led by Remi Cuchillo under Lee Gregory, who is Chief Data and Analytics Officer (CDAO) in Group...

In this role at EY, you will have the opportunity to contribute to the Supply Chain Technology group of the GDS consulting Team as a Staff Level Consultant with expertise in Generative AI. Your responsibilities will involve designing, developing, and fine-tuning Generative AI models using frameworks like LangChain, Hugging Face, TensorFlow, or PyTorch. Additionally, you will implement solutions for data pre-processing, tokenization, and dataset augmentation, and deploy Generative AI models on cloud platforms or edge devices to ensure scalability and robustness. You will work on MLOps pipelines, conduct performance benchmarking, hyperparameter tuning, and stay updated on the latest trends in ...

What would you be doing/ Expected from this role Collaborate with cross-functional teams including data scientists, engineers, and product managers to deliver AI-driven solutions. Drive the architecture of machine learning pipelines from data collection and preprocessing to model training, evaluation, and deployment. Implement scalable machine learning solutions using cloud infrastructure (AWS, GCP, Azure) and big data technologies (Spark, Hadoop). Develop and maintain model monitoring, alerting systems, and frameworks to ensure optimal performance in production. Stay up to date with the latest trends in AI and machine learning, identifying opportunities for innovation and improvement. Work ...

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience with ML design, ML architecture, and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Experience with Generative AI and AI Algorithms. Preferred qualifications: Experience in a specific ML domain relevant to the team's work, such as Natural Language Processing (NLP), Generative AI and Graph Neural Networks (GNNs). Experience with MLOps practices, including model monitoring, versioning and CI/CD pipelines for ML Experience in translating high-level business goals into concrete technical delivera...