Data Scientist

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