Company Highlights
- Work for a global company with excellent benefits and a dynamic culture.
- Excellent growth/advancement opportunity.
- Work with collaborative, successful colleagues who truly care about the work and each other while maintaining work-life balance.
Responsibilities
- Work with a product manager as technical lead of a team of ~5 engineers, data scientists, and analysts to design, scope, and oversee work in an Agile environment.
- Manage junior data and web engineers, focusing on productivity, quality, and professional development.
- Partner with the head of Data Strategy and other senior engineers to create and evangelize best-in-class engineering competency and tooling within the organization.
- Enforce strong development standards across the team through code reviews, automated testing, and monitoring.
- Establish strong relationships with internal clients as an engineering representative for data strategy.
- Contribute to the overall Data Strategy vision and execution via quarterly planning and executive committee reporting.
- Partner regularly improving engineering recruiting process for the required skillsets and resourcing demands.
- Learn the complex business of reinsurance to coach data technologists and execute the team's initiatives more effectively.
- Develop, implement, and deploy custom data pipelines powering machine learning algorithms, insights generation, client benchmarking tools, business intelligence dashboards, reporting, and new data products.
- Innovate new ways to leverage large and small datasets to drive revenue via the development of new products with the Data Strategy team, as well as the enhancement of existing products.
- Architect engineering solutions using the latest cloud technologies in a process that spans hypothesis-validating prototypes to large-scale production data products, ensuring internal security and regulatory compliance.
- Design solutions that account for unstructured data and document management system(s), including ingesting, tracking, parsing, analyzing, and summarizing documents at scale.
- Perform exploratory and goal-oriented data analyses to understand and validate the requirements of data products and help create product roadmaps.
- Develop, implement, and deploy front ends and APIs, which may involve business intelligence dashboards, data pipelines, machine learning algorithms, and file ingestion mechanisms.
Required Qualifications
- A minimum of 5 years of relevant experience in data-focused software engineering.
- Master’s Degree or Ph.D. in data science, computer science, or related quantitative field such as applied mathematics, statistics, engineering or operations research, or equivalent experience.
- Experience working with Python-based server-side web frameworks like FastAPI or Django.
- Strong knowledge of SQL and familiarity with the high-level properties of modern data stores.
- Strong understanding of the contemporary SDLC, including dev/QC/prod environments, unit/integration/UA testing, CI/CD, etc.
- Experience building and maintaining CI/CD pipelines with tools such as Azure DevOps, GitLab, Travis, Jenkins, etc.
- 2+ years of data analysis, AI, or data science work.
- Experience with data cleaning, enrichment, and reporting to business users.
- Extensive experience with (py)Spark, Python, JSON, and SQL.
- Experience integrating data from semi-structured and unstructured sources.
- Knowledge of various industry-leading SQL and NoSQL database systems.
- Experience with or strong interest in learning about LLMs in a productized context.
- At least one of the following sets of experience:
Data Engineering
- 2+ years’ experience with data engineering.
- Extensive experience with (py)Spark, Python, JSON, and SQL.
- Experience integrating data from semi-structured and unstructured sources.
- Knowledge of various industry-leading SQL and NoSQL database systems.
Backend Web
- 2+ years of backend/full-stack web engineering.
- Experience working with Python-based server-side web frameworks like FastAPI or Django.
- Experience with complex backends involving multiple data stores, asynchronous worker queues, pub-sub messaging, and the like.
- Knowledge of cloud-based web deployments (AWS/Azure/GCP, Kubernetes, auto-scaling, etc.).
- Experience with one or more major frontend frameworks (React strongly preferred).
Data Science/Analytics
- 2+ years of data analysis, AI, or data science work.
- Experience with data cleaning, enrichment, and reporting to business users.
- Experience selecting, training, validating, and deploying machine-learning models.
- Experience with or strong interest in learning about LLMs in a productized context.
- Experience working in an Agile environment to facilitate the quick and effective fulfillment of group goals.
- Good interpersonal and communication skills for establishing and maintaining sound internal relationships, working well as part of a team, and for presentations and discussions.
- Strong analytical skills and intellectual curiosity (interest in the meaning and usefulness of the data), as demonstrated through academic experience or work assignments.
- Excellent verbal and writing skills for complex communications with GC colleagues in all departments and levels of the organization, including communicating technical concepts to a non-technical audience.
Preferred Qualifications
- Strong understanding of entity resolution, streaming technologies, and ELT/ETL frameworks.
- Experience with web scraping and crowdsourcing technologies.
- Experience with Databricks and optimizing Spark clusters.
- Experience architecting web ecosystems from the ground up, including monolith vs. microservice decisions, caching technologies, security integrations, etc.
- Experience working with data visualization dashboarding tools (PowerBI, Tableau).
- Insurance domain knowledge or strong interest in developing it.
- Experience with the MS Azure cloud environment.
Benefits
Hybrid work is offered; employees may work remotely and collaborate in the office with at least three days onsite per week, with a designated anchor day for the full team.
The applicable base salary range for this role is $162,000 to $291,600.
The base pay offered will be determined on factors such as experience, skills, training, location, certifications, education, and any applicable minimum wage requirements. Decisions will be determined on a case-by-case basis. In addition to the base salary, this position may be eligible for performance-based incentives.
Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, veteran status (including protected veterans), or any other characteristic protected by applicable law. If you have a need that requires accommodation, please let us know by contacting
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