Data Scientist
Summary
As a Senior Data Scientist, you will develop advanced predictive models for insurance risk and extract insights from large datasets. Core technologies include Python, SQL, and distributed data platforms like Spark.
Key Responsibilities:
As a Senior Data Scientist, you will play a pivotal role in our data science efforts, with
responsibilities including, but not limited to, the following:
1. Advanced Analytics: Apply state-of-the-art data science techniques to analyze and extract meaningful
insights from vast and diverse datasets.
2. Predictive Modeling: Develop and implement advanced predictive models to forecast key risk factors
relevant to insurance and potentially other use cases.
3. Collaboration: Collaborate closely with our data engineers, product managers, and other business
stakeholders to translate data insights into actionable strategies and solutions.
4. Data Visualization: Create compelling data visualizations and reports to communicate findings effectively to
both technical and non-technical audiences.
5. Research and Innovation: Stay at the forefront of data science research, exploring new methodologies and
technologies to drive innovation within the company.
Requirements:
• 3-5 years proven track record as a Data Scientist working with large datasets (e.g., millions of rows), from
prototyping to business impact, analytics and ML use cases
• Deep understanding of machine learning and statistical methods with their underlying theory and math
• Demonstrated experience in building, deploying, and showing business value from predictive models and
data products
• Highly proficient in Python
• Proficiency in SQL databases, understanding schemas, and data types
• Real-world experience with at least one distributed data platform (preferably Spark)
• Solid software development experience, including translating ML models into production software,
especially in collaboration with other engineers
• MS or PhD in a quantitative discipline, especially Statistics, Math, or similar
• Strong communication skills
Desirable Skills:
• Deep Learning, especially Transformers
• Experience with GLMs, including for actuarial frequency applications
• Boosting algorithms (CatBoost, XGBoost, etc)
• Experience with distributed machine-learning frameworks, like Spark, etc.
• Creating data pipelines for analytics or ML applications
• Experience using AWS (EC2, EMR, S3, etc) or similar cloud provider (Google, Azure, etc.)
• Resourceful self-starter and team player with strong leadership skills
• Uncompromising attention to details
• Proven ability to be creative and resourceful in a fast-paced, entrepreneurial environment
• Must be comfortable working independently
• React well and quickly to frequent project demands and requirement changes
• Excellent analytical, troubleshooting, and problem-solving skills
• Strong written and communication skills and positive attitude working with customers and partners