Senior Data Scientist
Skills
Computer ScienceBusiness IntelligenceData AnalyticsHealthcareModelingProduction SupportRepositories
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 4–7 years of experience building statistical or machine learning models using large datasets
- Advanced degree in Computer Science Engineering or relevant field
- PhD in Data Science or another quantitative field preferred
- Advanced proficiency in Python R and SQL
- Strong hands-on experience with regression GLM tree-based methods boosting clustering and basic text analytics
- Proven experience developing validating and tuning models for real-world use cases
- Experience supporting models in production environments
- Solid understanding of model evaluation experimental design and performance metrics
- Strong data wrangling skills with large complex datasets
- Ability to create clear compelling data visualizations and analytical narratives
- Ability to translate business problems into analytical approaches with limited guidance
- Strong written and verbal communication skills
- Experience following best practices for reproducible research version control and documentation
- Ability to provide constructive peer feedback and informal mentorship
- Demonstrated curiosity and willingness to learn new tools methods and domains
Nice to have
- Curious
- Analytical
- Collaborative
- Detail-oriented
- Mentoring-minded
Day to day
- Lead advanced statistical and machine learning initiatives to solve complex healthcare business problems using large-scale datasets
- Own the end-to-end analytical process from problem framing and feature engineering to model development validation and refinement
- Partner with data engineering and cross-functional teams to operationalize models monitor performance and support scalable production solutions