Senior Analytics Engineer, Data Strategy
New York - 1166
Company:
Guy CarpenterDescription:
We are seeking a talented individual to join our Data Strategy team at Guy Carpenter. This role will be based in New York, NY; Boston, MA or Philadelphia, PA. This is a hybrid role that has a requirement of working at least three days a week in the office.
The Data Strategy team is a multidisciplinary team that aims to cultivate and build on the data assets across all functions and lines of business globally within Guy Carpenter, Marsh McLennan's reinsurance brokerage. The Senior Analytics Engineer bridges data engineering and data science, where expertise lies in the knowledge of the underlying data and its analysis, transformation, and visualization. This position directs how data will be used in pipelining, applications, decision-making, and machine-learning models while sharing responsibilities with product managers in direct customer engagement.
We'll count on you to:
Work with stakeholders to define their data challenges and business needs, and drive the integration and adoption of our data products.
Conduct exploratory data analysis and provide deep understanding of our business with conclusions and recommendations that show a high level of critical thinking
Critically analyze data and identify trends, such as spotting user behavior patterns to inform product improvements, while also demonstrating a basic understanding of product design and user experience.
Work with the development teams and the product managers to design and implement new features based on user feedback.
Remain current on analytics technology innovations and identify how they can create business value.
What you need to have:
5+ years of experience as a data analyst or analytics engineer and 2+ years of experience with data modeling (preferably in dbt)
Strong proficiency in SQL and Python; Familiarity with machine learning, in particular natural language processing
Working knowledge of ETL/ELT and REST API principles, and schema design across source systems, data lakes, and dashboards
Experience with cloud data platforms such as Azure Data Lake, Databricks, or other equivalent MPP tools like Snowflake or BigQuery; Familiarity with data reporting and visualization tools such as PowerBI, Tableau, or Looker
What makes you stand out:
Experience on a high-performing data team at a technology, consulting, or start-up company
Experience delivering either client-facing analytic tools or applications
Insurance knowledge or strong interest in building insurance domain knowledge
Why join our team:
We help you be your best through professional development opportunities, interesting work and supportive leaders.
We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.
Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
Job Profile
3 days in office Hybrid role Hybrid work
Benefits/PerksCareer opportunities Disability Employee Assistance Programs Flexible work Flexible work environment Health and welfare Health and welfare benefits Hybrid work Inclusive culture Interesting work Professional development Professional development opportunities Supportive leaders Training Tuition Assistance Well-being rewards
Tasks- Analyze data trends
- Conduct exploratory data analysis
- Data Analysis
- Define data challenges
- Design and implement features
- Training
Advising Analysis Analytics Azure Azure Data Lake BigQuery Brokerage Cloud data platforms Collaboration Consulting Critical thinking Data analysis Databricks Data Lake Data Modeling Data Strategy Dbt ELT Engineering ETL Insurance Insurance Knowledge Integration Looker Machine Learning Natural Language Processing Power PowerBi Power BI Python Reinsurance Reporting REST API Retirement programs Schema design Snowflake SQL Strategy Tableau Training
Experience5 years
Education Certifications TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9