REGISTRIEREN

Jobbörse

Finde Jobs in deiner Nähe – ob vor Ort, hybrid oder remote.
  • Ähnliche Jobs zu: Senior Predictive Liability Analytics Lead
XX
Senior Predictive Liability Analytics LeadAmerican General Life Insurance Company • Los Angeles, California, United States
Jetzt Bewerben
XX

Senior Predictive Liability Analytics Lead

American General Life Insurance Company
  • US
    Los Angeles, California, United States
  • US
    Los Angeles, California, United States
Jetzt Bewerben

Über

Position Overview
Senior Predictive Liability Analytics Lead
– Balance Sheet Risk Management (BSRM). You will build next‑generation short‑term models of policyholder behavior, collaborate across finance and actuarial teams, and lead design and deployment of predictive models. Responsibilities
Design predictive and semi‑structural models focused on short‑term behavior and long‑horizon outcomes using GLMs, GAMs, survival models, tree ensembles, and deep learning. Extract features from structured and unstructured data (contracts, correspondence, transcripts) utilizing NLP, transformer embeddings, RAG pipelines, LLMs, generative‑AI, and evolutionary algorithms. Make models scenario‑aware by incorporating drivers such as credited rate, market spreads, surrender charge state, and channel effects; calibrate elasticity to economic conditions. Translate outputs into curves/driver functions consumable by projection engines (Moody’s AXIS, Aon Pathwise, Prophet, RAFM, internal models). Support valuation, pricing, ALM, and capital teams in sensitivity analyses and assumption updates. Build training and scoring pipelines on Databricks/Spark/Snowflake/AWS using Python and SQL; track experiments with MLflow/DVC, version in Git, package with containers, and deploy via batch/API. Develop dashboards for calibration, drift, stability, and bias; establish retraining schedules, fallback models, and automated alerts. Co‑design experiments (A/B, uplift, causal inference) and explore contextual bandits or RL for intervention timing and messaging. Support actuarial, finance, and capital on scenario stress, attribution, and sensitivity runs; present results to governance committees and internal validation. Skills & Qualifications
Master’s or PhD in Statistics, Data Science/ML, Applied Math, Computer Science, or Actuarial Science; FSA/ASA a plus. 7+ years building production predictive models in insurance or annuity environments, with documented wins in behavior modeling (surrender, utilization, lapse). Strong knowledge of ML/AI tools: Python (pandas, NumPy, scikit‑learn, XGBoost/LightGBM, PyTorch/TensorFlow), SQL, R, NLP/LLM frameworks, Databricks, Spark, Snowflake, AWS/Azure. Experience with model governance, reproducibility, version control, and MLOps using MLflow, model registries, CI/CD pipelines. Excellent communication, documentation, and mentoring skills; ability to balance accuracy, interpretability, and operational simplicity. Compensation
Base salary range: $190,000 – $210,000; discretionary bonus eligible. Compensation depends on location, experience, and other factors. Work Location & Travel
Hybrid role based in Woodland Hills, CA or New York, NY. Minimal travel ( Equal Opportunity Employer
Corebridge Financial is an equal‑opportunity employer and complies with all applicable fair‑employment laws. All qualified applicants will receive consideration without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability, age, veteran status, or other protected characteristic. Corebridge Financial is committed to providing reasonable accommodations to applicants and employees, including those with disabilities or sincerely held religious beliefs. Appropriate accommodations are determined on a case‑by‑case basis following applicable federal, state, and local law.
#J-18808-Ljbffr
  • Los Angeles, California, United States

Sprachkenntnisse

  • English
Hinweis für Nutzer

Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.