Data Scientist - Product Development

Job Description

Must have skills required :Experience with AI/ML tools and frameworksGood to have skills :NLP, AI/ML, R PythonGRADATIM (One of Uplers Clients) is Looking for:Data Scientist Product Development who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you.Role Overview DescriptionSeeking a technical Data Scientist to build, implement, and integrate advanced ML/AI solutions (model development, data analysis, AI features) into insurance products, collaborating across teams.Key Responsibilities :ML/Model Development: Design, build, optimize ML models (risk, fraud, claims, underwriting) using various algorithms; feature engineering, tuning, validation.Data Engineering: Process data, build/optimize ETL pipelines using cloud platforms (AWS/Azure/GCP).Algorithm Implementation: Develop/optimize AI/ML algorithms (incl. Deep Learning, RL) for production. Integration/Deployment: Deploy models (API/microservices), use MLOps, collaborate with DevOps/Eng. Research & Innovation: Stay updated on AI/ML trends, experiment with tools. Collaboration & Documentation: Work with PMs/Engineers, document processes, communicate findings.Required EducationMasters or Bachelors in Data Science, Computer Science, Statistics, or related field.Required Technical Skills Programming: Python or R (strong proficiency) ML Libraries: TensorFlow, PyTorch, Scikit-learn Data: SQL, NoSQL, Data Pipelines (Spark, Hadoop, Airflow) Cloud ML: AWS SageMaker, Azure ML, or GCP Vertex AI MLOps: Familiarity (e.g., MLflow, Kubeflow, TensorBoard)Required KnowledgeModel evaluation metrics, statistical analysis, optimization techniques.Preferred Skills Experience in NLP, Computer Vision, Deep Learning (for insurance). Familiarity with Graph Analytics (for fraud/network analysis). Knowledge of insurance processes or financial risk modeling. Must have skills required :Experience with AI/ML tools and frameworksGood to have skills :NLP, AI/ML, R PythonGRADATIM (One of Uplers Clients) is Looking for:Data Scientist Product Development who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you.Role Overview DescriptionSeeking a technical Data Scientist to build, implement, and integrate advanced ML/AI solutions (model development, data analysis, AI features) into insurance products, collaborating across teams.Key Responsibilities :ML/Model Development: Design, build, optimize ML models (risk, fraud, claims, underwriting) using various algorithms; feature engineering, tuning, validation.Data Engineering: Process data, build/optimize ETL pipelines using cloud platforms (AWS/Azure/GCP).Algorithm Implementation: Develop/optimize AI/ML algorithms (incl. Deep Learning, RL) for production. Integration/Deployment: Deploy models (API/microservices), use MLOps, collaborate with DevOps/Eng. Research & Innovation: Stay updated on AI/ML trends, experiment with tools. Collaboration & Documentation: Work with PMs/Engineers, document processes, communicate findings.Required EducationMasters or Bachelors in Data Science, Computer Science, Statistics, or related field.Required Technical Skills Programming: Python or R (strong proficiency) ML Libraries: TensorFlow, PyTorch, Scikit-learn Data: SQL, NoSQL, Data Pipelines (Spark, Hadoop, Airflow) Cloud ML: AWS SageMaker, Azure ML, or GCP Vertex AI MLOps: Familiarity (e.g., MLflow, Kubeflow, TensorBoard)Required KnowledgeModel evaluation metrics, statistical analysis, optimization techniques.Preferred Skills Experience in NLP, Computer Vision, Deep Learning (for insurance). Familiarity with Graph Analytics (for fraud/network analysis). Knowledge of insurance processes or financial risk modeling.

Keyskills :
NLPPythonData analysisDeep LearningReinforcement LearningAIML toolsFeature engineeringETL pipelines