Data Scientist, Consumer Lines- Insurance

Key Skills

Data science techniques, Database, Machine learning techniques, MLOps tools, Pandas, Predictive analytics, Python Programming, Scikit-learn, SQL, TensorFlow

Job Description

We are seeking an experienced and innovative Data Scientist with 3-5 years of hands-on experience to join our dynamic team. The ideal candidate will have a strong background in data science, proficiency in Python, Azure, SQL and Git and expertise in Predictive Modelling and Machine Learning Algorithms. If you are passionate about leveraging cutting-edge technologies to solve complex problems and have a proven track record in developing and deploying machine learning models, we want to hear from you.

Responsibilities

• Design, develop, and deploy machine learning solutions to meet enterprise goals and support experimentation and innovation.
• Evaluate and fine-tune machine learning models to achieve optimal performance metrics. Conduct experiments and A/B testing to improve model performance and explore different algorithmic approaches.
• Present the data science solutions to business stakeholders using presentation and data visualization techniques.
• Building and managing pipelines to deploy and monitor machine learning solutions.
• Working closely with CloudOps and MLOp teams to deploy Machine Learning solutions.
• Monitoring and maintenance of models – building pipelines for recalibration and deploying recalibrated models whenever required
• Mine and analyse data from company databases to drive optimization and improvement of product development and business strategies.

Qualifications

Desired Qualifications

• Minimum of a bachelor’s degree, preferably in Statistics, Mathematics, Analytics or Computer Science. Advanced degree in Statistics or Predictive Analytics is strongly preferred.
• 3 - 5 years of experience as Data Scientist, preferably in the insurance industry.
• Python proficiency including developing complex python functions and python classes to enable code to run within an automated framework.
• Strong analytical thinking and problem-solving skills, with the ability to translate complex data into actionable insights.
• Strong proficiency in Python language with experience in data transformation and modelling libraries (e.g., pandas, scikit-learn, TensorFlow).
• Excellent communication skills, with the ability to effectively convey complex findings to both technical and non-technical stakeholders.
• Knowledge of SQL and database management systems for data extraction and manipulation.