Axiom Pro is a leading recruiting and outstaffing company. One of our distinguished U.S.-based clients, a provider of trusted life insurance solutions with over 1.6 million policyholders, is committed to long-term financial security and innovation. The organization holds an A (Excellent) rating from AM Best and is focused on driving sustainable growth through data-driven decision-making.
We are currently seeking a highly analytical and results-oriented Senior Data Scientist to join the company’s Marketing Analytics team.
Responsibilities
– Build and maintain predictive models for customer behavior (purchase propensity, policy premium, lapse/retention, cross-sell, upsell, next-best-action).
– Conduct advanced exploratory data analysis.
– Perform model interpretability and explainability analysis.
– Evaluate model performance using metrics such as precision, recall, and F1 score.
– Implement A/B testing and experimental design.
– Apply model fairness, bias mitigation, and ethical AI principles.
– Ensure compliance with data privacy regulations (GDPR, CCPA).
– Analyze model and campaign performance using both test datasets and production results.
– Forecast campaign outcomes and validate forecasts against actual results.
– Collaborate with data engineers and architects to ensure high-quality data for modeling.
– Develop and maintain data pipelines.
– Perform feature engineering and data preparation.
– Identify and integrate external datasets to improve models.
– Maintain documentation of models, data sources, and analytical results.
– Automate analytical workflows and improve efficiency of existing processes.
– Conduct ad-hoc analysis to support marketing distribution and strategy.
– Identify opportunities for new models and analytical initiatives.
Requirements
– Master’s degree in Statistics, Economics, Mathematics, Data Science, or related field.
– 5–7 years of experience in Data Science or Machine Learning.
– Experience with marketing analytics or customer behavior modeling.
– Strong proficiency in Python or R for statistical analysis and machine learning.
– Strong SQL skills for data extraction and data manipulation.
– Experience with machine learning frameworks (scikit-learn, TensorFlow, PyTorch, Databricks, DataRobot).
– Experience with AI/ML platforms such as AWS SageMaker or similar tools.
– Experience with cloud platforms (AWS, Azure, Google Cloud).
– Familiarity with big data technologies (Spark, Hadoop).
– Experience with advanced modeling techniques (ensemble methods, time series analysis, probabilistic modeling).
– Experience with model deployment and monitoring tools.
– Experience with data visualization tools (Power BI, Tableau, or similar).
– Strong analytical thinking and problem-solving skills.
– Ability to communicate complex technical results to non-technical stakeholders.
– Experience working in cross-functional teams.
Preferred Experience:
– Experience in insurance or financial services.
– Experience applying Generative AI in predictive modeling.
– Experience with marketing attribution models and marketing mix modeling.
– Experience with customer lifetime value modeling and customer churn prediction.
– Experience with MLOps and automated model deployment.
– Experience using Git and CI/CD pipelines.
– Knowledge of actuarial modeling or risk assessment principles.
Mandatory Skills
– Big Data
– Data Analysis
– Python
– Data Visualization
– Statistics
– SQL
– AWS
– Machine Learning
Mandatory Languages
– English
Working Day
– Full Time Job
Working Conditions
– Monthly payments on Payoneer/PayPal/crypto;
– Working schedule: Monday to Friday.
– The standard working day is 8 hours, with maximum overlap with the Eastern Time Zone expected during the working hours.
– The position is offered as a freelance contract.
– Days off and vacations are granted upon prior approval from the employer.