Data Scientist - Product Development

Must have skills required :

Experience with AI/ML tools and frameworks

Good to have skills :

NLP, AI/ML, R Python

GRADATIM (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 Description

Seeking 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 Education

Masters 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 Knowledge

Model 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.