Data Scientist Regional Data Science Team (with Actuarial exposure)

Job Description

As a Data Scientist in the Regional Data Science Team with Actuarial exposure at LII, you will have the opportunity to shape the future of AI by tackling real business challenges that matter in your region. You will be an integral part of a dynamic team that delivers innovative, AI-powered solutions to create measurable impact for local business lines. Your role will involve collaborating with experienced data scientists, actuaries, engineers, and business leaders to accelerate experimentation and drive high-value projects aligned with regional priorities.**Key Responsibilities:**- Collaborate with regional data science, actuarial, and business teams to design and execute time-boxed experiments and analyses addressing high-priority insurance business challenges.- Support the delivery of key data science and actuarial solutions by applying statistical and actuarial methods to real-world problems in pricing, risk assessment, claims, and reserving.- Build and validate predictive models and actuarial analyses using Python, leveraging libraries such as pandas, NumPy, scikit-learn, and actuarial modeling techniques.- Stay flexible and responsive, adapting quickly to evolving business needs and focusing on high-value deliverables directed by your Regional Data Science Manager.- Help manage and prioritize your teams project backlog, balancing new opportunities with critical business timelines.- Analyze results and develop insights that demonstrate ROI and practical impact for local business lines, presenting findings effectively to both technical and non-technical stakeholders.- Contribute to the standardization and improvement of modeling, reporting, and analytical processes in collaboration with regional teams and the Center of Excellence.- Work closely with actuaries, data scientists, engineers, IT, and business stakeholders globally to share knowledge and leverage best practices.- Stay proactive about emerging trends in AI, data science, actuarial science, and MLOps, bringing fresh ideas to the team.**Qualifications:**- Bachelors or Masters degree in Actuarial Science, Data Science, Mathematics, Statistics, Computer Science, Engineering, or a related field.- Around 3 years of hands-on experience in data science and/or actuarial analysis, preferably in insurance or related financial services.- Practical experience in Python for statistical modeling, data manipulation, and machine learning, along with exposure to actuarial software or techniques.- Strong analytical and problem-solving skills with the ability to translate insurance business questions into robust data science and actuarial solutions.- Understanding of core actuarial concepts like loss modeling, rate-making, risk classification, reserving, and exposure analysis.- Ability to effectively communicate technical findings and insights to various audiences.- Demonstrated flexibility and adaptability to pivot quickly and work on pressing business deliverables as priorities change.- Eagerness to learn, innovate, and contribute to a collaborative, high-energy team environment.- Progress towards actuarial credentials (such as ASA, ACAS, or equivalent) is a plus. As a Data Scientist in the Regional Data Science Team with Actuarial exposure at LII, you will have the opportunity to shape the future of AI by tackling real business challenges that matter in your region. You will be an integral part of a dynamic team that delivers innovative, AI-powered solutions to create measurable impact for local business lines. Your role will involve collaborating with experienced data scientists, actuaries, engineers, and business leaders to accelerate experimentation and drive high-value projects aligned with regional priorities.**Key Responsibilities:**- Collaborate with regional data science, actuarial, and business teams to design and execute time-boxed experiments and analyses addressing high-priority insurance business challenges.- Support the delivery of key data science and actuarial solutions by applying statistical and actuarial methods to real-world problems in pricing, risk assessment, claims, and reserving.- Build and validate predictive models and actuarial analyses using Python, leveraging libraries such as pandas, NumPy, scikit-learn, and actuarial modeling techniques.- Stay flexible and responsive, adapting quickly to evolving business needs and focusing on high-value deliverables directed by your Regional Data Science Manager.- Help manage and prioritize your teams project backlog, balancing new opportunities with critical business timelines.- Analyze results and develop insights that demonstrate ROI and practical impact for local business lines, presenting findings effectively to both technical and non-technical stakeholders.- Contribute to the standardization and improvement of modeling, reporting, and analytical processes in collaboration with regional teams and the Center of Excellence.- Work closely with actuaries, dat

Keyskills :
PythonActuarial ScienceData ScienceMathematicsStatisticsComputer Science