Lead Data Scientist

Criteria’s 

Job Requirements 

General Job Description 

As the Lead Data Scientist in Sapiens, your primary responsibility is to spearhead the development and implementation of cutting-edge data analytics and machine learning solutions to drive informed decision-making and enhance overall business performance. You will lead a team of data scientists in leveraging advanced statistical models and predictive analytics to assess risk, optimize pricing strategies, and streamline underwriting processes. Collaborating closely with cross-functional teams, you will play a pivotal role in identifying opportunities to leverage data for business growth, customer retention, and fraud detection.  

Additionally, as a key stakeholder in the development of data-driven strategies, you will contribute to the continuous improvement of underwriting models, claims processing, and customer segmentation. With a focus on innovation, you will stay abreast of industry trends and emerging technologies, ensuring that the organization remains at the forefront of data science advancements within the insurance sector. Your leadership will be instrumental in driving a culture of data-driven decision-making and fostering collaboration between data science and other business functions to achieve strategic objectives. 

Pre - requisites Knowledge & Experience 

• Master's or Ph.D. in Computer Science, Statistics, or a related field. 
• 3+ years of experience as Lead Data Scientist. 
• Proficient in statistical modeling, machine learning algorithms, and data manipulation techniques relevant to insurance analytics.  
• Experience in deploying models to production, ensuring scalability, reliability, and integration with existing business processes. 
• Previous background in working with AI/ML models with Insurance industry. 
• Proficiency in Python and relevant libraries/frameworks (e.g., TensorFlow, PyTorch). 
• Familiarity with big data platforms (e.g., Hadoop, Spark) for handling and analyzing large datasets efficiently. 
• Solid understanding of data management, governance, and security. 
• Knowledge of regulatory compliance in AI/ML practices. 

Required Product/project Knowledge 

• Understanding of the insurance industry and its processes. 
• Knowledge of data science, statistics and machine learning applications in the insurance domain 

Required Skills 

• Programming: Proficient in Python. 
• Tools/Frameworks: Experience with 3 out of DataBricks, ML Flow, TensorFlow, PyTorch, GPT, LLM and other relevant tools. 
• Leadership: Ability to lead and mentor a team. 
• Strategic Thinking: Develop and execute AI/ML strategies aligned with business objectives. 
• Data Management: Ensure data availability and quality for model training. 
• Evaluation: Assess applicability of AI/ML technologies and recommend tools/frameworks 

Common Tasks 

• Collaborate with product managers, customers, and other stakeholders. 
• Implement monitoring systems for model performance. 
• Evaluate and recommend AI/ML technologies. 
• Oversee model development from ideation to deployment. 
• Collaborate with IT and data governance teams. 

Required Soft Skills 

• Leadership: Lead and mentor a team of data scientists and engineers. 
• Communication: Collaborate with cross-functional teams and stakeholders. 
• Innovation: Drive innovation in AI/ML strategies for insurance products. 
• Adaptability: Stay updated on the latest advancements in AI/ML technologies. 
• Ethics: Ensure AI/ML practices comply with industry regulations and ethical standards.