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We are looking for a Senior Data Scientist who will play a critical role in driving applied AI/ML strategy to optimize commercial lines insurance operations.
Important: selected specialist can be based anywhere as long as she/he can work during core collaboration hours (8:30 am - 2:30 pm Pacific Time.)
Location: 100% remote
B2B up to 175 PLN net+vat/h
Must have:
- Higher degree in Data Science, Statistics, Computer Science etc.
- Fluent English
- Minimum 5 years of experience as a Data Scientist, preferably in the insurance industry
- Expertise in statistical modeling, predictive analytics, machine learning, and data mining techniques.
- Proficiency in Python with data manipulation and visualization libraries experience
- Experience with large-scale data processing frameworks and databases (Snowflake, SQL, Vector DBs, Knowledge Graphs)
- Advanced problem-solving skills, with the ability to analyze complex datasets and derive meaningful insights
- Communication and collaboration abilities
- Ability to present ideas/solutions 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
Main Responsibilities:
- Lead the creation and execution of data-driven strategies to enhance our underwriting methods, pricing frameworks, risk evaluations, and customer experience initiatives.
- Examine extensive and intricate datasets to uncover patterns, trends, and potential risk factors for clients that align with our products or may affect our loss ratios.
- Utilize statistical modeling and predictive analytics to develop models that improve the precision and efficiency of insurance risk evaluations and pricing decisions.
- Work alongside multidisciplinary teams, including actuaries, underwriters, data and infrastructure engineers, and IT experts, to advance data-focused projects and cultivate a culture of AI-enhanced, data-informed decision-making.
- Develop and implement machine learning algorithms and artificial intelligence techniques to automate and refine processes such as prospect identification, policy review and evaluation, claims processing, and presentation of client insights.
- Offer guidance and mentorship to analysts and data engineers, encouraging knowledge sharing and professional growth within the team.
- Instruct and mentor leaders and colleagues from other departments on the possible applications of ML/AI technologies in their fields.
- Keep abreast of industry trends, new technologies, and best practices in data science and insurance analytics to foster ongoing improvement and innovation.