Senior Director and Actuary, Asset & Liability Management & Investment Strategy (ALM & IS)
Remote, any state, US
Job Requisition ID: 90892
Location Designation: Fully Remote
Location: This is a fully remote position reporting to New York Life's headquarters in New York City. Applicants may work from a home office anywhere in the United States.
Offered salary: $223,500.42
Duties: Researches and develops data analytics, machine-learning, and stochastic models and methods for asset liability management (ALM) and investment strategy. This includes exploration and consolidation of internal and external data (i.e., life insurance and annuity products, market, and portfolio performance), developing models for predicting cashflows, asset allocation, risk management, and models for automating liability hedging decisions. Works with the Chief Investment Office, Corporate Finance, Actuarial, Credit Risk, Data Science, and IT to design, build, implement, and communicate quantitative solutions to a less-technical audience. Mentors junior staff, performs resource allocation, and develops training programs. Assists internal stakeholders and leadership to make business decisions related to asset-liability management and investment strategy.
Requirements: Master's degree in Mathematics, Statistics, Actuarial Science, Computer Science or related quantitative field (willing to accept foreign education equivalent) plus three years of experience in performing financial engineering, asset & liability management and balance sheet, advanced machine-learning, artificial intelligence, and quantitative risk management and modeling within the life insurance, banking or investment industry
or, alternatively, a Bachelor's degree in Mathematics, Statistics, Actuarial Science, Computer Science or related quantitative field (willing to accept foreign education equivalent) and five years of experience in performing financial engineering, asset and liability management and balance sheet, advanced machine-learning, artificial intelligence, and quantitative risk management and modeling within the life insurance, banking or investment industry.
Experience must include 3 years in each of the following skills: Developing ALM, balance sheet projection models and frameworks, balance sheet, and profit & loss (P&L) impact analysis leveraging mathematical and statistical methods (including loss models and optimization models) to evaluate risk-reward measures for long-dated assets and liabilities; Developing and implementing credit and market risk management and actuarial models for life insurance leveraging time series analysis, Monte-Carlo simulation, non-linear optimization, and quasi-Monte Carlo, regression, principal component analysis, hypothesis tests, model selection, and interpolation advanced statistical methods, and coding in Python, R or C++; Processing complex life insurance customer, transactional, and valuation data structures from multiple databases, augmented with external data and developing metadata and extract, transform, load (ETL) processes to create model-ready datasets leveraging Python, R or SQL; and, Developing and implementing machine-learning (ML) and artificial intelligence (AI) models, including deep-learning neural networks leveraging Python and structured and unstructured data to predict financial metrics (including cash flows, lapse rate across different products, duration, and default probability) and to improve and automate ALM processes, and coding in Python, R or C++.
Special Skills, License/Certification: Must possess Associate of the Society of Actuaries (ASA) and Fellow of the Society of Actuaries (FSA) certification (or foreign equivalent actuarial certification).
Eligible for Employee Referral Program.
Pay Transparency
Overtime eligible: Exempt
Discretionary bonus eligible: Yes
Sales bonus eligible: No
Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program.
Our Benefits
We provide a full package of benefits for employees – and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs. Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work. Click here to discover more about our comprehensive benefit options or visit our NYL Benefits Site.
Our Diversity Promise
We believe in a diverse workforce because it is our mission to advocate for the financial security and success of people in every community. This is why diversity, equity, and inclusion (DEI) are guiding principles that are embedded in our brand and our culture. Click here to learn more about how we have been recognized for our leadership.
Recognized as one of Fortune’s World’s Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. To learn more about career opportunities at New York Life, please visit the Careers page of www.NewYorkLife.com.
ApplyJob Profile
Fully remote
Benefits/PerksAdoption Assistance Annual discretionary bonus Benefits Discretionary bonus Discretionary bonus eligible Employee giving Employee Referral Program Financial Security Fully remote Incentive Program Leave programs Overtime eligible Pay Transparency Sales bonus Sales bonus eligible Student Loan Repayment Student loan repayment programs Training programs Volunteerism
Tasks- Assist stakeholders in decision making
- Develop data analytics and models
- Mentor junior staff
- Optimization
- Reporting
- Training
Actuarial science AI Analysis Analytics Artificial Intelligence Asset liability management C C++ Computer Data & Analytics Deep Learning Engineering ETL Extract transform load (ETL) Finance Financial engineering Hypothesis tests Insurance Interpolation IT Leadership Life Insurance Machine Learning Mathematics Model Selection Monte Carlo simulation Non-linear optimization Principal component analysis Python Quantitative risk management R Regression Reporting Risk Management Sales Security SQL Statistics Stochastic models Technical Time Series Analysis Training Training Programs
Experience5 years
EducationBachelor's Bachelor's degree Business Computer Science Equivalent Finance Master's Master's degree Mathematics
CertificationsASA Associate of the society of actuaries (ASA) Fellow of the society of actuaries (FSA) FSA
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9