Data Science Trainee - Global Analytics at Chubb

, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

03 May, 26

Salary

0.0

Posted On

02 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Large Language Models, Deep Learning, NLP, Machine Learning Models, Data Collection, Model Deployment, Supervised Learning, Unsupervised Learning, Ensemble Techniques, Hyperparameter Tuning, Random Forest, XGBoost, SVM, Azure Cloud Computing, Docker

Industry

Insurance

Description

About Chubb Chubb is a world leader in insurance. With operations in 54 countries and territories, Chubb provides commercial and personal property and casualty insurance, personal accident and supplemental health insurance, reinsurance and life insurance to a diverse group of clients. The company is defined by its extensive product and service offerings, broad distribution capabilities, exceptional financial strength and local operations globally. Parent company Chubb Limited is listed on the New York Stock Exchange (NYSE: CB) and is a component of the S&P 500 index. Chubb employs approximately 43,000 people worldwide. Additional information can be found at: www.chubb.com. About Chubb India At Chubb India, we are on an exciting journey of digital transformation driven by a commitment to engineering excellence and analytics. We are proud to share that we have been officially certified as a Great Place to Work® for the third consecutive year, a reflection of the culture at Chubb where we believe in fostering an environment where everyone can thrive, innovate, and grow. With a team of over 2500 talented professionals, we encourage a start-up mindset that promotes collaboration, diverse perspectives, and a solution-driven attitude. We are dedicated to building expertise in engineering, analytics, and automation, empowering our teams to excel in a dynamic digital landscape. We offer an environment where you will be part of an organization that is dedicated to solving real-world challenges in the insurance industry. Together, we will work to shape the future through innovation and continuous learning. Position Details: Function/Department: Advanced Analytics Location: Bangalore, India Employment Type: Full-time Role Overview – Data Scientist Trainee Chubb is seeking a Data Science trainee to develop and scale our Generative AI capabilities. The ideal candidate will be responsible for designing, finetuning and training large language models and developing Generative AI systems that can create and improve conversational abilities and decision-making skills of our machines Major Responsibilities: Develop and improve Generative AI systems to enable high quality decision making, to refine answers for queries, and to enhance automated communication capabilities. Own the entire process of data collection, training, and deploying machine learning models. Continuous research and implementation of cutting-edge techniques in deep learning, NLP and Generative AI to build state-of-the-art models. Work closely with Data Scientists and other Machine Learning Engineers to design and implement end-to-end solutions. Optimize and streamline deep learning training pipelines. Develop performance metrics to track the efficiency and accuracy of deep learning models. Sound understanding of ML concepts, Supervised / Unsupervised Learning, Ensemble Techniques, Hyperparameter Good knowledge of Random Forest, XGBoost, SVM, Clustering, building data pipelines in Azure/Databricks, deep learning models, OpenCV, Bert and new transformer models for NLU, LLM application in ML> Strong experience with Azure cloud computing and containerization technologies (like Docker, Kubernetes).

Responsibilities

The trainee will be responsible for designing, finetuning, and training large language models and developing Generative AI systems to enhance machine conversational abilities and decision-making skills. This includes owning the entire process from data collection and training to deploying machine learning models and researching cutting-edge deep learning techniques.