34 Job openings found

About the RoleThe Senior Model Risk Analyst in the Market Risk function under the Risk business unit is responsible for assessing and validating quantitative models used across Treasury, Wholesale, and Retail functions. These models, which support internal decision-making and product disbursement, are governed by the bank’s Model Risk Management framework. ...

  Experience Range: 5 to 12 yrs (min 4 years relevant) Responsibilities: Enable Model tracking, model experimentation, Model automation Develop ML pipelines to support  Develop MLOps components in Machine learning development life cycle using Model Repository (either of): MLFlow, Kubeflow Model Registry Machine Learning Services (either of): Kubeflow, DataRobot, HopsWorks, Dataiku or any relevant ML E2E PaaS/SaaS. Work ...

Chemical Engineer with vast experience as process technologist in petrochemical/ chemical/pharmaceuticals process in R&D. • Possess proven R&D skills for various chemical / polymer process technology development / transfer technology.  Core Skills: • Experience in setting up laboratories and experimental set ups for high temperature high pressure gas-liquid-solid catalyzed reactions, laboratory and ...

Exp- 5 -8 yrs Client- HSBC Designation- AM/M (30 Manager/  22 AM) Location- Bangalore only Work Mode- Hybrid ( 2 days from client office) UK Shift. REQ ID-3388   Key Responsibilities: Lead model development projects, ensuring adherence to policy and standards Review projects, guide analysts and managers, and provide analytical support Act as a subject matter expert in model development and ...

  Roles and Responsibilities Preforming Risk Analytics activities to develop models and support the bank on various analytical initiatives Assist in modeling key risk estimates PD, LGD and EAD for AIRB and IFRS9 framework Regularly engage in model development, validation, and re-development activities Other risk analytics activities include assisting in review and re-development of Macro-Economic ...

JOB SUMMARYLooking for highly skilled and experienced Senior Data Architect. As a Senior Data Architect,you will play a critical role in designing, implementing, and managing data architecture,ensuring it supports both current needs and future aspirations in data and AI. This rolerequires a deep understanding of data architecture principles, data modelling ...

Key Responsibilities  Model Development & Training  ○ Design, train, and fine-tune deep learning and machine learning models (transformers, CNNs, RNNs, gradient boosting, etc.).  ○ Implement data preprocessing pipelines, feature extraction, and  augmentation techniques.  ○ Conduct hyperparameter optimization and experiment management. ● Evaluation & Optimization  ○ Run model evaluations, benchmark against baselines, and perform ablation studies.  ○ ...

Key Responsibilities: - 1. Model Development: Design, build, and optimize supervised, unsupervised, and deep learning models for various business problems. 2. Data Exploration & Feature Engineering: Clean, transform, and analyze structured and unstructured data; identify significant features. 3. AI Integration: Develop end-to-end AI pipelines and integrate models into production systems ...

Credit Risk Analytics and Modelling – Analyse, model, validate and document various measures of Credit Risk for use in Expected Credit Loss and Capital computations. Hands-on experience in building, implementing, documenting, monitoring, validating, refining models and scorecards – in particular for PD, LGD, EAD and related Credit Risk metrics - using ...

About the Role : We are looking for a hands-on Full Stack Data Scientist who can independently manage the  entire machine learning lifecycle—from data wrangling to deployment—without relying on a  dedicated data engineering team. This role is ideal for someone who thrives in a fast-paced, self- directed environment and is passionate about building real-world ML solutions that drive  business outcomes.      Key Responsibilities : ∙Own the full ML pipeline: data ingestion, cleaning, feature engineering, model  development, deployment, and monitoring.  ∙Build and fine-tune models using Python and frameworks like Scikit-learn, XGBoost,  TensorFlow, or PyTorch.  ∙Deploy models using Databricks, MLflow, and cloud-native tools (preferably Azure).  ∙Develop robust, scalable pipelines using PySpark or native Databricks workflows.  ∙Collaborate with BI analysts and business stakeholders to translate requirements into  production-ready solutions.  ∙Maintain and improve existing models and pipelines with minimal supervision.      Required Skills : ∙3+ years of experience in applied data science or ML engineering.  ∙Strong Python programming skills, including experience with data manipulation and ML libraries.  ∙Experience with Databricks and cloud-based ML deployment (Azure preferred).  ∙Ability to work independently across the full stack of ML development and deployment.    ∙Familiarity with version control (Git), CI/CD, and MLOps best practices.  ∙Excellent communication skills and ability to work with remote teams across time zones.      Nice to Have  ∙Experience with data pipeline development using PySpark or Delta Lake.  ∙Exposure to Docker, REST APIs, or real-time inference.  ∙Prior experience working in a manufacturing or industrial analytics environment.    Interview Process:  Shortlisted candidates will be required to complete:  ∙An online technical skills assessment focused on Python and applied machine learning.  ∙An in-person practical test at our Ahmedabad Tech Center to evaluate real-world  problem-solving and deployment capabilities.  Hours: 2:30 PM – 11:30 PM IST (working from Office) Reports to: Manager, Data Analytics California, USA