Associate Actuary and SME I - Actuarial Pricing
- Bangalore, Karnataka
- Permanent
- Full-time
- Develop, calibrate, and implement technical models using GLMs and more advanced statistical techniques, incorporating relevant variables and factors for accurate pricing and risk assessment.
- Analyse historical insurance data to identify patterns and trends, and determine the impact of various factors on the models.
- Conduct rate level reviews to ensure appropriate pricing of insurance products, considering risk exposure, market dynamics, and profitability goals.
- Collaborate with cross-functional teams to understand business objectives and identify areas where data-driven solutions can drive revenue, growth, renewals, and/or claims efficiency.
- Enhance technical models over time by incorporating new data sources, refining variables, and exploring innovative modelling techniques.
- Evaluate the impact of pricing strategies, policy changes, and market shifts on portfolio performance, and make recommendations for adjustments, if needed.
- Present findings and recommendations to stakeholders, including senior management and underwriting teams, in clear and concise reports and presentations.
- Work closely with other departments including Underwriting, Claims, Actuarial, Finance, and Risk Management, providing them with the data and insights needed to make evidence-based decisions.
- Bachelor's degree (or equivalent) degree in a quantitative field such as Actuarial Science, Statistics, or Mathematics.
- 5+ years of related practical experience, preferably in the commercial insurance sector.
- Showing good exam progress under one of the Actuarial Societies is preferred.
- Strong proficiency in statistical modelling techniques, specifically GLMs, and experience with software tools like R or Python.
- Solid understanding of insurance pricing principles, loss reserving, and risk assessment methodologies.
- Familiarity with insurance industry regulations, standards, and best practices.
- Excellent analytical and problem-solving skills, with the ability to translate data into meaningful insights and recommendations.
- Strong communication skills to effectively convey complex findings and recommendations to both technical and non-technical stakeholders.
- Attention to detail and ability to work independently, managing multiple projects and deadlines efficiently.
- Proficiency with data analysis and visualisation tools and platforms will be an added advantage, preferably QlikView/Qliksense, Power BI, etc.
- Develop, calibrate, and implement technical models using GLMs and more advanced statistical techniques, incorporating relevant variables and factors for accurate pricing and risk assessment.
- Analyse historical insurance data to identify patterns and trends, and determine the impact of various factors on the models.
- Conduct rate level reviews to ensure appropriate pricing of insurance products, considering risk exposure, market dynamics, and profitability goals.
- Collaborate with cross-functional teams to understand business objectives and identify areas where data-driven solutions can drive revenue, growth, renewals, and/or claims efficiency.
- Enhance technical models over time by incorporating new data sources, refining variables, and exploring innovative modelling techniques.
- Evaluate the impact of pricing strategies, policy changes, and market shifts on portfolio performance, and make recommendations for adjustments, if needed.
- Present findings and recommendations to stakeholders, including senior management and underwriting teams, in clear and concise reports and presentations.
- Work closely with other departments including Underwriting, Claims, Actuarial, Finance, and Risk Management, providing them with the data and insights needed to make evidence-based decisions
- Bachelor's degree (or equivalent) degree in a quantitative field such as Actuarial Science, Statistics, or Mathematics.
- 5+ years of related practical experience, preferably in the commercial insurance sector.
- Showing good exam progress under one of the Actuarial Societies is preferred.
- Strong proficiency in statistical modelling techniques, specifically GLMs, and experience with software tools like R or Python.
- Solid understanding of insurance pricing principles, loss reserving, and risk assessment methodologies.
- Familiarity with insurance industry regulations, standards, and best practices.
- Excellent analytical and problem-solving skills, with the ability to translate data into meaningful insights and recommendations.
- Strong communication skills to effectively convey complex findings and recommendations to both technical and non-technical stakeholders.
- Attention to detail and ability to work independently, managing multiple projects and deadlines efficiently.
- Proficiency with data analysis and visualisation tools and platforms will be an added advantage, preferably QlikView/Qliksense, Power BI, etc.