Data Scientist - Remote

Data Science & Advanced Analytics
• Synthesize large, complex datasets to uncover trends, assess business impact, and recommend data-driven improvements.
• Design and build statistical and machine learning models to support Life Insurance use cases such as:
○ Pricing and product profitability
○ Underwriting risk assessment
○ Lapse & persistency prediction
○ Customer lifetime value (CLV)
○ Cross-sell and upsell optimization
• Build GLM-based and other statistical models aligned with Life Insurance actuarial and pricing methodologies.
• Develop explanatory, predictive, and forecasting models using descriptive and inferential statistics, regression, and machine learning techniques.
• Research, evaluate, and implement appropriate statistical and mathematical methodologies for business problems.

Data Preparation & Exploration
• Perform data validation, preprocessing, feature engineering, and exploratory data analysis (EDA).
Ensure model inputs are accurate, scalable, and compliant with business and regulatory requirements.
Leadership & Mentorship
• Provide guidance and mentorship to junior data scientists and analysts.
• Promote best practices in model development, documentation, and knowledge sharing.

Technical & Analytical Skills
• Extensive experience with supervised and unsupervised machine learning algorithms, including Generalized Linear Models (GLMs).
• Strong understanding of predictive and prescriptive analytics.
• Advanced experience in:
○ Data manipulation and feature engineering
○ Exploratory data analysis
○ Model development and solution design
• Strong programming experience in Python.
• Strong programming experience in SQL.
• Working knowledge of Git version control.
• Ability to communicate effectively with both technical and non-technical audiences in written, oral, and presentation formats.
• Strong problem-solving skills with the ability to multi-task and learn quickly

Preferred Qualifications
• Prior experience in Life Insurance actuarial, pricing, underwriting, or risk analytics.
• Advanced knowledge of model tuning, evaluation, validation, and operationalization (MLOps).
• Experience designing and consuming APIs at scale.
• Hands-on experience with cloud and big data technologies, such as:
○ Databricks / Spark
○ Azure, AWS, or GCP
○ Snowflake
• Experience with Deep Learning frameworks (TensorFlow / Keras, PyTorch, MXNet).
• Experience in Text Analytics and Natural Language Processing (NLP) (e.g., claims notes, underwriting documents).
• Comfortable with command-line environments (Linux / Windows scripting).
Experience with additional programming languages (e.g., R, Scala, Julia, Go, Java, or C++).

Education
• Graduate degree preferred in Statistics, Computer Science, Data Science, Mathematics, Economics, Engineering, or a related technical field.
Equivalent practical experience will be considered

- Receive 100% salary from the onboarding date.
- Participate in company activities: Monthly and quarterly parties, teambuilding, travel, vacation and other activities.
- Work with large and advanced systems, have the opportunity to develop comprehensive technology skills with complex problems, requiring high accuracy.