Due to covid-19, it will be remote for now. Post covid-19 consultant should work onsite
Job description :
- Work with data engineers, IT teams and business partners to assemble data from various sources into datasets to analyze the information to source Inforce and other related data to create Model inforce feed
- Provide support to data quality and data validation through analysis of data and assisting in understanding the meaning of data.
- Perform data profiling on large sets data stored on Hadoop platform.
- Administer and generate metrics on data to monitor and improve the quality of data.
- Participate in changes to key data elements and source data and document the changes to business and technical definitions and data lineage in our metadata repository.
- Should be able to explore data to find its meaning and relationship to solving business problems:
- Document technical and business data definitions and data lineage from source to target in a metadata management system.
- Work with peer technical personnel, members of the DAO team, and our business partners to assemble data from various sources into datasets to analyze the information to solve business problems and improve business efficiency.
- Support technical and business testing as a member of development project teams.
- Administer and generate metrics on data to monitor and improve the quality of data.
- Participate in changes to key data elements and source data and document the changes to business and technical definitions and data lineage in our metadata repository.
Job Requirements:
- Excellent written, verbal, and interpersonal skills, a must as there will be significant collaboration with the business and IT
- Multi-line Life Insurance and Annuity experience is required for working with business to understand business impact for data issues
- Experience in creating dashboards with data quality key performance indicators (KPIs)
- Relevant experience in at least one of the following areas are desired:
- Connecting, wrangling, and cleaning data from relational, columnar, or Hadoop databases using SQL, Python, R, or other tools to make data consumable for analysis. You can automate and document your processes to make them repeatable.
- Creating metadata: Defining the meaning of data and analyzing data flows to determine source to target data lineage, then storing this information in a metadata reference library. Documenting data entity relationships in a tool such as Excel, Erwin, etc..
- Analyzing data to obtain new insights that will lead to improved efficiencies, lower cost, or reduced business risk. You may be using Excel, Python, R, SQL / HQL and other tools. You may be able to visualize your results using data visualization tools to make your conclusions more understandable to your audience.
- Analyzing the statistical relationship of data to a problem to be solved using SQL, Python, or R. Determine new and creative sources of data and then determining the comparative strength of the relationship to the problem after the new data is applied.
Preferred Skills:.
- Training or degree in Data Analysis, Data Engineering or Statistical Modeling.
- Experience in exploratory data analysis and how data analysis fits into an analytic lifecycle desired.
- Experience in metadata management with a metadata management tool (such as IBM Infosphere tool suite).
Relevant IT or other technical experience in data analysis/mapping, logical and physical data modeling preferred.