Informacje o stanowisku
As a Senior Data Scientist, you will play a critical role in driving our applied AI/ML strategy to optimize our commercial lines insurance operations. Your expertise in statistical modeling, predictive analytics, machine learning, and data mining will be essential to identify patterns, extract insights, and develop innovative solutions that enhance our underwriting, pricing, and risk management processes. By leveraging advanced data analysis techniques, you will contribute to maintaining our low loss ratios, improving efficiency of our sales, underwriting, and client servicing operations, and delivering value to our clients, employees, and investors.
This role can be based anywhere as long as you can work our Devopsbay core collaboration hours (8:30 am-2:30 pm Pacific Time.)
Responsibilities :
- Lead the development and implementation of data-driven solutions that improve our underwriting processes, pricing models, risk assessment, and client experience strategies.
- Analyze large, complex datasets to identify patterns, trends, and potential client risk factors that align with our product offerings or could impact our loss ratios.
- Apply statistical modeling and predictive analytics techniques to create models that enhance the accuracy and efficiency of insurance risk assessments and pricing decisions.
- Collaborate with cross-functional teams, including actuaries, underwriters, data and infrastructure engineers, and IT professionals, to drive data-centric initiatives and foster a culture of data-driven, AI-enhanced decision-making.
- Design and implement machine learning algorithms and artificial intelligence techniques to automate and optimize operational processes, such as prospect identification, policy assessment and evaluation, claims management and client insight presentation.
- Provide guidance and mentorship to analysts and data engineers, promoting knowledge sharing and skill development within the team.
- Educate and mentor functional leaders and peers in other departments on the potential applications of ML/AI technologies to their domains.
- Stay up-to-date with industry trends, emerging technologies, and best practices in data science and insurance analytics to drive continuous improvement and innovation.
About you:
- Masters or Ph.D. in Data Science, Statistics, Computer Science, or a related field.
- 6+ years of experience as a Data Scientist, preferably in the insurance industry, with a focus on commercial lines.
- Strong expertise in statistical modeling, predictive analytics, machine learning, and data mining techniques.
- Proficiency in programming languages such as Python, as well as experience with data manipulation and visualization libraries.
- Experience with large-scale data processing frameworks and databases (e.g., Snowflake, SQL, Vector DBs, Knowledge Graphs) is a plus.
- Excellent problem-solving skills, with the ability to analyze complex datasets and derive meaningful insights.
- Strong communication and collaboration abilities, with the capability to present technical concepts to both technical and non-technical stakeholders.
- Leadership qualities and the ability to guide and mentor junior team members and more senior stakeholders and peers.
Nice to have:
- Exposure to and passion for early-stage startups and/or high growth environments
- A background in insurance or other regulated categories
Project Stack & Tools
Backend
- TypeScript, Python, Prisma, NestJs, Ruby on Rails, SQL, Terraform, Spark
Frontend
Databases & Data Processing
- PostgreSQL, Snowflake, Airflow, DBT, Mode, Stitch
Testing
- Jest, Vitest, Playwright, RSpec
CI/CD & Deployment
- CircleCI, Nomad, Docker, Docker Compose
Monitoring & Logging
- LogRocket, Datadog, Rollbar, LaunchDarkly, AWS CloudWatch
Cloud & Infrastructure
- AWS (Lambdas, SQS, ECS, IAM), Kafka, Okta, AWS Athena (Nice to have)
Collaboration & Design
- GitHub, Figma, Atlassian Stack (Jira, Confluence, OpsGenie)
AI & Machine Learning
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