Senior Predictive Liability Analytics Lead

Senior Predictive Liability Analytics Lead Hybrid - CA-Woodland Hills Mar 10, 2026 $190K - $210K Group: Balance Sheet Risk Management (BSRM) Reports to: Head of Actuarial Strategy & Integration About the role Join BSRM as our hands‑on Senior Predictive Liability Analytics Lead. You’ll build next‑gen short‑term models of policyholder behavior starting with annuity surrenders, withdrawals, and utilization. You’ll collaborate with other stakeholders such as financial planning, ALM, pricing, valuation and capital as appropriate. This is a technical leadership role (not initially a people‑manager or strategy role). You’ll do the math, write the code, build models, and mentor by example. Responsibilities Design predictive and semi‑structural models with a short‑term focus (performance focused on fitting the next 18‑36 months) on long‑horizon behavior (surrenders, partial withdrawals, lapse, rider utilisation) using GLMs/GAMs, survival & hazard models (Cox, discrete‑time, competing risks), tree ensembles (Boost/LightGBM/CatBoost), and deep learning choosing the most appropriate tool depending on the business problem. Leverage unstructured data (contract text, correspondence, customer relationship notes, call transcripts) via NLP/transformer embeddings, RAG pipelines, and LLM‑assisted document parsing to create novel behavioural features within guardrails. Pilot generative‑AI (foundation models) for feature extraction/summarisation; use genetic/evolutionary algorithms for feature selection, architecture search, or synthetic cohort generation when appropriate. Make models scenario‑aware: incorporate drivers like credited rate, market rate spreads, moneyness, surrender charge state, distribution channel effects; calibrate elasticity to economic conditions documented in industry studies. Translate model outputs into curves/driver functions consumable by projection engines (e.g., Moody’s AXIS, Aon Pathwise, Prophet, RAFM, or internal models); generate reproducible, versioned results tables. Share models with valuation/projection/ALM teams so behaviour sensitivities can be considered alongside assumptions that normally flow through cash‑flow projections, LDTI assumption updates, RBC/CTE stresses, and hedge effectiveness studies. Partner with valuation and pricing to reconcile actual vs. expected and attribute earnings/variance to behaviour; document the “model story” and explainability for governance. Build training/scoring pipelines in Python/SQL on Databricks/Spark/Snowflake/AWS; track experiments with MLflow/DVC, version in Git, package with containers, and serve via batch/API. Stand up dashboards for calibration, drift, stability, and bias; set retraining schedules, fallback models, rollback criteria, and automated alerts. Co‑design experiments (A/B, uplift, causal inference) with Business Owners/Operations/Distribution to test interventions; when warranted, explore contextual bandits/RL for offer timing and messaging. Support Actuarial/Finance/Capital on scenario stress, attribution, and sensitivity runs; including helping to present results to model governance, assumption committees, and internal validation as needed. Skills & Qualifications Certifications in ML/AI (nice to have). 7–10+ years building production predictive models; insurance/annuity or long‑duration liability exposure preferred. Practical wins in behaviour modeling (surrender/utilisation/lapse) and integration. Comfortable spanning structured + unstructured data and bridging to projection engines. Clear, concise communicator; strong documentation habits; bias to ship and iterate. Mentors by example; sets standards for code quality, reproducibility, and testing. Balances accuracy, interpretability, and operational simplicity under governance. Collaborate within a highly matrixed organisation. NLP/LLM: transformers/embeddings, RAG, prompt engineering; genetic/evolutionary search for features/hyper‑params. Databricks/Spark, Snowflake, AWS/Azure; MLflow, model registries, CI/CD; Tableau/Power BI for monitoring & storytelling. Working familiarity with Actuarial platform (AXIS/Prophet/RAFM/etc.) integration patterns (assumption tables, mapping layers). Compensation The anticipated salary range for this position is $190,000 to $210,000 at the commencement of employment. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered will ultimately be dependent on multiple factors, which may include the candidate’s geographic location, skills, experience and other qualifications. In addition, the position is eligible for a discretionary bonus in accordance with the terms of the applicable incentive plan. Corebridge also offers a range of competitive benefits as part of the total compensation package. Work Location This position is based in Corebridge Financial’s Woodland Hills or New York office and is subject to our hybrid working policy, which gives colleagues the benefits of working both in an office and remotely. Minimal travel. Benefits Health and Wellness: Medical, dental and vision insurance plans, as well as mental health support and wellness initiatives. Retirement Savings: US 401(k) Plan offers a generous dollar‑for‑dollar Company matching contribution of up to 6% of eligible pay and a Company contribution equal to 3% of eligible pay (subject to annual IRS limits and Plan terms). These contributions vest immediately. Employee Assistance Program: Confidential counselling services and resources are available to all employees. Matching Charitable Donations: Corebridge matches donations to tax‑exempt organisations 1:1, up to $5,000. Volunteer Time Off: Employees may use up to 16 volunteer hours annually. Paid Time Off: Eligible employees start off with at least 24 Paid Time Off (PTO) days. We are an Equal Opportunity Employer Corebridge Financial is committed to being an equal opportunity employer and we comply with all applicable federal, state, and local fair employment laws. All applicants will be considered for employment based on job‑related qualifications and without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, disability, neurodivergence, age, veteran status, or any other protected characteristic. The Company is also committed to compliance with all fair employment practices regarding citizenship and immigration status. Corebridge Financial is committed to working with and providing reasonable accommodations to job applicants and employees, including any accommodations needed on the basis of physical or mental disabilities or sincerely held religious beliefs. If you believe you need a reasonable accommodation in order to search for a job opening or to complete any part of the application or hiring process, please send an email to View email address on click.appcast.io. Reasonable accommodations will be determined on a case‑by‑case basis, in accordance with applicable federal, state, and local law. We will consider for employment qualified applicants with criminal histories, consistent with applicable law. Estimated Travel Percentage (%): Up to 25% #J-18808-Ljbffr