Senior Data Scientist- Data Suite R D

This position will be part of Sapiens Digital (Data Suite) division, for more information about it, click here:

We are looking for an enthusiastic Senior Data Scientist with a foundational understanding of data science principles and an interest in the insurance industry. The role involves working alongside senior data scientists to analyze data, build models, and generate insights.

What youll do:

Data Exploration & Preparation

• Collect, clean, and preprocess data from internal and external sources, ensuring data quality and consistency for model development.
• Identify patterns and insights through exploratory data analysis (EDA) and feature engineering.

Model Development & Evaluation

• Develop predictive models to improve accuracy
• Apply machine learning and deep learning techniques.

Model Deployment & Monitoring

• Deploy machine learning models in a production environment and work with MLOps teams to ensure continuous monitoring and model updates.
• Set up model performance metrics and tracking mechanisms to address model drift or changing data trends.

Cross-functional Collaboration

• Work closely with different teams to translate business objectives into data science solutions.
• Collaborate with IT and engineering teams for data integration, model deployment, and scaling requirements.

Presentation & Stakeholder Engagement

• Present data-driven insights and actionable recommendations to business leaders, demonstrating the business value and impact of analytical findings.
• Develop and deliver regular reporting to stakeholders, showcasing model effectiveness and areas for improvement.

What to Have for this position.

Must have Skills.

• Education: Masters in Data Science, Statistics, Mathematics, Actuarial Science, Computer Science, or a related field.
• Experience: Minimum of 5-7 years of experience in data science or analytics roles, with at least 3 years specifically within the insurance industry (life, health, property, or casualty insurance).
• Industry Knowledge: Solid understanding of insurance-specific concepts such as underwriting, claims management, policy lifecycle, customer segmentation, fraud detection, and risk assessment.
• Compliance Awareness: Familiarity with insurance regulations (e.g., GDPR, HIPAA, IRDA guidelines) and an understanding of privacy requirements for handling Personally Identifiable Information (PII) and other sensitive data

• Insurance Product Knowledge: In-depth knowledge of insurance products, policy structures, customer lifecycle, and the factors affecting claims and risk assessments.
• Claims Prediction & Fraud Detection Models: Experience with building models for claims forecasting, fraud detection, customer churn, and customer lifetime value (CLTV).
• Customer Segmentation & Underwriting Models: Proficiency in creating risk segmentation, customer profiling, and underwriting models to improve customer targeting and policy recommendations.
• Insurance Data Types: Familiarity with both structured and unstructured data sources commonly used in the insurance industry, including policy records, claims data, customer interactions, agent notes, and IoT data from wearables or telematics (for auto insurance).

• Statistical & Machine Learning Expertise: Advanced knowledge of statistical methods, machine learning algorithms, and deep learning techniques.
• Programming Languages: Proficiency in Python for data analysis and model building, along with SQL for data extraction and manipulation.
• Data Engineering Basics: Familiarity with ETL processes and the ability to work with large datasets
• Modeling & Analytical Tools: Experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and statistical software
• Platforms: Proficiency in cloud environments (AWS, Azure, or GCP) for scalable data processing and model deployment. Knowledge of DataBricks will be preferred.

Required Soft Skills :

• Business Acumen: Ability to understand business requirements and map them into data science solutions that provide tangible value.
• Problem-Solving: Proactive and innovative in problem-solving, especially in translating complex data insights into clear and actionable business recommendations.
• Communication Skills: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Collaboration & Teamwork: Ability to work effectively within a cross-functional team environment.
• Adaptability: Willingness to keep up with the latest developments in data science and adapt to changing project needs.
• Attention to Detail: High level of accuracy and attention to detail in data analysis and model building, ensuring reliable outcomes.

About Sapiens :

Sapiens is a global leader in the insurance industry, delivering its award-winning, cloud-based SaaS insurance platformto over 600 customers in more than 30 countries. Sapiens platform offers pre-integrated, low-code capabilities to accelerate customers digital transformation. With more than 40 years of industry expertise, Sapiens has a highly professional team of over 5,000 employees globally.

For More information visit us on .

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