About the job Actuarial Manager
We're hiring for Actuarial Manager preferably from Insurance Industry.
About Our Client:
Our client company is one of a leading US based Software House. Specialized in US Healthcare Software Products.
Job Description
As a Manager/Lead Data Analytics - Actuarial, you will be responsible for driving data-driven strategies by leveraging advanced analytics, predictive modeling, and data insights to optimize insurance operations. Your role will focus on cost prediction, future trend analysis, and risk assessment to enhance decision-making processes. You will work closely with cross-functional teams to design and implement analytics solutions that improve operational efficiency, customer experience, and financial forecasting.
Key Responsibilities
- Develop and implement advanced analytics solutions to optimize cost prediction and risk assessment in insurance operations
- Build predictive models and machine learning algorithms to analyse market trends
- Design and develop data visualization dashboards and reports to effectively communicate complex insights to stakeholders
- Analyze large datasets to uncover patterns, correlations, and business opportunities that drive strategic decisions
- Collaborate with IT and business teams to integrate analytics-driven solutions into existing systems
- Ensure data integrity, governance, and compliance with industry regulations and risk management standards
- Stay updated with emerging technologies, AI-driven analytics, and best practices in insurance analytics
Job Requirements
- Education: Bachelors or Masters degree in Actuarial Sciences, Data Science, or a related field
- Experience: Minimum 8+ years of experience in the insurance industry, focusing on analytics, cost prediction, and forecasting.
Technical Skills:
- Proficiency in data analytics tools such as SQL, Python, R, or SAS
- Experience with predictive modeling, machine learning and statistical forecasting
- Hands-on experience with BI tools like Power BI, Tableau, or Looker for data visualization
- Strong understanding of data governance, data management, and real-time data analytics.
Industry Knowledge:
- Expertise in cost modeling, claims analysis, and risk forecasting for insurance operations
- Exposure to regulatory compliance, actuarial risk assessment, and financial impact analysis.
Soft Skills:
- Strong analytical mindset with problem-solving abilities focused on cost and future trend prediction
- Excellent communication and stakeholder management skills for presenting data-driven insights
- Ability to work in a fast-paced, tech-driven environment and align analytics strategies with business goals
- Leadership qualities to mentor junior analysts and drive data-driven decision-making across teams
Preferred Background
- Prior experience in the insurance industry or companies associated with insurance, particularly in cost analysis and predictive analytics
- A personality that aligns with the tech industry, demonstrating adaptability, innovation, and data-driven strategic thinking.
Other Details:
Work Mode: Onsite - Full Time
Location: Lahore
Experience: 8+ years
Days: Monday to Friday
Timing: 9 AM -6 PM
Salary: Market Competitive
Benefits
- Provident Fund
- Medical Coverage (IPD)
- Vehicle Benefit (Car)
- EOBI
- Leaves Encashment
- Bi-Annual Performance Increment
- Bi-Annual Performance Bonus
- Referral Bonus
- Meal Allowance
- Internet Allowance (3000 Rupee)
- Late Sitting Allowance
- Hardship Allowance
- Certifications & Trainings (Udemy & Internal)
- Recreational & Extracurricular Activities
About HR Ways:
HR Ways is an Award winning Technical Recruitment Firm helping software houses and IT Product companies internationally and locally to find IT Talent. HR Ways is engaged by 300+ Employers worldwide ranging from worlds biggest SaaS Companies to most competitive Startups. We have entities in Dubai, Canada, US, UK, Pakistan, India, Saudi Arabia, Portugal, Brazil and other parts of the world. Join our WhatsApp Channel https://shorturl.at/983azto stay updated or visit www.hrways.co to know more.