Location: Bangalore, India
About Us
Sapiens International Corporation (NASDAQ and TASE: SPNS) is a leading global provider of software solutions for the insurance industry, with a growing presence in the financial services sector. We offer integrated core software solutions and business services, and a full digital suite for the property and casualty/general insurance; life, pension, and annuities; and reinsurance markets. Sapiens also services the workers’ compensation and financial and compliance markets.
Our portfolio includes policy administration, billing, and claims; underwriting, illustration and electronic application; reinsurance and decision management software. Sapiens’ digital platform features customer and agent portals, and a business intelligence platform. With a 40-year track record of delivering to more than 700 organizations, Sapiens’ team of over 5,500 employees operates through our fully-owned subsidiaries in North America, the United Kingdom, EMEA, and Asia Pacific. For more information: www.sapiens.com.
Sapiens Digital team is developing Sapiens' next generation of insurance online services, enabling insurance companies to accelerate their digital services to customers and agents. The Digital team is focused on developing online capabilities for insurance companies on any platform, mobile, and web covering a wide range of self-service, commerce solutions aimed at optimizing the customers’ experience during engagements with their insurance companies & agents via digital channels.
For more information about Sapiens: https://www.sapiens.com/solutions-categories/data-and-digital/
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.