Senior Data Scientist - Insurance Analytics

Senior Data Scientist – Insurance Analytics (Remote – Nigeria)

Location: Anywhere in Nigeria (remote) – Based in Akure, Ondo (home office)
Industry: Insurance (property & casualty, life, health, and specialty lines)
Employment Type: Full‑time, permanent

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About the Role

Our client, a market‑leading innovator in the insurance sector, is looking for a Senior Data Scientist with deep expertise in insurance analytics. You will own the end‑to‑end lifecycle of data‑science projects that drive underwriting, claims, pricing, fraud detection, and customer‑retention strategies. Working closely with actuaries, product managers, business analysts, and IT engineers, you will turn massive, heterogeneous data sets into actionable insights that shape the company’s competitive edge.

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Key Responsibilities

• Data Exploration & Feature Engineering

  • Identify, ingest, and curate new internal & external data sources (telemetry, IoT, social, third‑party APIs).
  • Conduct thorough exploratory data analysis (EDA) and develop robust feature pipelines for modeling.

• Model Development & Validation

  • Design, build, and fine‑tune statistical and machine‑learning models (GLMs, GAMs, survival models, gradient boosting, random forests, deep learning, etc.) for loss cost, claim severity, frequency, fraud detection, churn, and customer‑lifetime‑value.
  • Implement time‑series forecasting for premium revenue, reserve estimation, and risk trends.
  • Perform rigorous model validation, back‑testing, and stress‑testing in line with regulatory and internal governance standards.

• Production & Deployment

  • Translate prototypes into production‑ready pipelines using Spark, Airflow, Docker/Kubernetes, and cloud services (AWS, Azure, GCP).
  • Monitor model performance post‑deployment, set up automated drift detection, and trigger model retraining as needed.

• Collaboration & Communication

  • Partner with actuaries to embed domain knowledge into model assumptions and interpretability.
  • Translate complex analytical results into clear, business‑focused recommendations for senior leadership and non‑technical stakeholders.
  • Mentor junior data scientists and contribute to the team’s best‑practice documentation and code‑review processes.

• Research & Innovation

  • Stay abreast of emerging techniques (e.g., graph neural networks for fraud networks, reinforcement learning for dynamic pricing) and evaluate their applicability to insurance problems.

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Required Qualifications

Requirement	Details
Education	Master’s or Ph.D. in Statistics, Data Science, Mathematics, Computer Science, Actuarial Science, or a related quantitative field.
Experience	≥ 5 years of professional data‑science experience, with a strong focus on insurance analytics (underwriting, claims, pricing, fraud, or retention).
Programming	Advanced proficiency in Python (pandas, NumPy, scikit‑learn, PySpark, TensorFlow/PyTorch) or R (tidyverse, caret, data.table).
SQL	Expert‑level SQL for data extraction, transformation, and performance tuning.
Big‑Data & Cloud	Hands‑on experience with Spark (PySpark/Scala) and cloud platforms (AWS, Azure, or GCP) – e.g., S3/Blob storage, EMR/Databricks, SageMaker, Azure ML.
Statistical Modeling	Proven track record with GLMs, GAMs, survival analysis, Bayesian methods, and time‑series forecasting.
Machine Learning	Deep knowledge of gradient boosting (XGBoost, LightGBM), random forests, ensemble methods, and neural networks.
Model Governance	Familiarity with model risk management, documentation, and regulatory compliance (e.g., NAIC, GDPR).
Communication	Excellent written and verbal communication; ability to convey technical concepts to business audiences.
Teamwork	Demonstrated ability to collaborate across cross‑functional teams (actuaries, product, IT).

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Desired (but not mandatory) Skills

• Experience with MLOps tools (MLflow, Kubeflow, CI/CD pipelines).
• Knowledge of graph analytics for fraud network detection.
• Exposure to reinforcement learning for dynamic pricing or policy recommendation.
• Familiarity with Actuarial software (e.g., Prophet, GGY AXIS) or actuarial reserving techniques.
• Certifications: AWS Certified Machine Learning – Specialty, Azure AI Engineer Associate, or similar.

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What We Offer

• Fully remote work arrangement – work from anywhere in Nigeria (home office stipend provided).
• Competitive salary + performance‑based bonuses.
• Comprehensive health & wellness benefits.
• Professional development budget (conferences, certifications, courses).
• Collaborative, data‑driven culture with direct impact on business strategy.
• Cutting‑edge technology stack and access to large, real‑world insurance datasets.

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How to Apply

If you are passionate about turning complex insurance data into strategic advantage and thrive in a remote, high‑impact environment, we want to hear from you.

1. Submit your CV highlighting relevant insurance analytics projects.
2. Attach a cover letter describing a successful end‑to‑end data‑science project you led (problem, methodology, impact).
3. Include links to any GitHub/Portfolio showcasing code, notebooks, or model documentation (optional but encouraged).

Email: careers@insurance‑innovators.ng
Subject line: Senior Data Scientist – Insurance Analytics – [Your Name]

Application deadline: [Insert Date – typically 2‑3 weeks from posting]

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Our client is an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.